[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2004":3,"related-2004":80},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":22,"secondary_topics":28,"classification":29,"search_phrases":50,"slug":51,"view_count":52,"doi":53,"paper":54,"created_at":79},2004,"Evaluating the thermal impacts of urban corridor redevelopment and greening interventions in Addis Ababa using multi-temporal satellite data and machine learning","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cacint.2026.100465","Rapid urbanization and infrastructure expansion are fundamentally reshaping land surface thermal dynamics in Sub-Saharan African metropolises, yet the combined microclimatic impacts of simultaneous urban greening and corridor redevelopment remain understudied. This study systematically evaluated the spatiotemporal thermal and biophysical changes in Addis Ababa, Ethiopia, driven by the Corridor Development Projects between 1990 and 2025. Utilizing multi-temporal Landsat satellite imagery, we employed Random Forest machine learning classification alongside the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) to quantify land-use and land-cover (LULC) transformations, surface temperature variations, and ecological severity via the Urban Thermal Field Variance Index (UTFVI). Over the 35-year period, built-up areas expanded nearly fourfold from 14.8% to 53.3%, primarily encroaching upon agricultural lands, while net vegetation cover contracted from 13.8% to 8.1%. Consequently, mean Land Surface Temperature (LST) increased by 5.06 °C (from 29.43 °C to 34.49 °C), expanding severe ecological heat stress (UTFVI ≥ 0.02) to 48.0% of the municipal area, with Bole, Akaki-Kality, and Kirkos emerging as considerable vulnerability hotspots. Bivariate spatial correlations confirmed strong cooling effects driven by elevation (r = −0.60 to − 0.68) and vegetation (r = −0.57 to − 0.71), contrasting with intense surface heating from built-up density (r = 0.54 to 0.63). The surface urban heat island (SUHI) intensity for Addis Ababa increased consistently from 0.40 °C in 1990 to 1.31 °C in 2025, reflecting faster urban warming than rural areas and a strengthening SUHI effect at an estimated rate of 0.026 °C per year over the study period. These findings expose a vital socio-ecological trade-off: localized corridor greening alters microclimate structure but cannot fully counterbalance city-wide warming from impervious surface expansion. Integrating thermal comfort metrics and minimum vegetation cover ratios into spatial planning is essential for climate-resilient urban development.","快速城市化与基础设施扩张正在从根本上重塑撒哈拉以南非洲大都市的地表热力动态，然而，城市绿化与廊道再开发同步进行所产生的综合微气候影响仍未得到充分研究。本研究系统评估了1990年至2025年间，在廊道开发项目驱动下，埃塞俄比亚亚的斯亚贝巴地表热力与生物物理特征的时空变化。利用多时相Landsat卫星影像，我们采用随机森林机器学习分类方法，结合归一化植被指数（NDVI）与归一化建筑指数（NDBI），量化了土地利用与土地覆盖（LULC）的转变、地表温度变化，并通过城市热场变异指数（UTFVI）评估了生态严重程度。在35年研究期内，建设用地面积从14.8%扩展至53.3%，增长了近四倍，主要侵占农业用地，而净植被覆盖面积则从13.8%缩减至8.1%。相应地，平均地表温度（LST）升高了5.06°C（从29.43°C升至34.49°C），严重生态热胁迫（UTFVI ≥ 0.02）范围扩大至全市面积的48.0%，其中博莱、阿卡基-卡利提和基尔科斯成为显著的脆弱性热点区域。双变量空间相关性分析证实，海拔（r = −0.60至−0.68）和植被（r = −0.57至−0.71）具有显著的降温效应，而建设用地密度则产生强烈的增温作用（r = 0.54至0.63）。亚的斯亚贝巴地表城市热岛（SUHI）强度从1990年的0.40°C持续增强至2025年的1.31°C，反映出城市升温速度快于农村地区，且SUHI效应在研究期内以约每年0.026°C的速率持续增强。上述发现揭示了一个关键的社会-生态权衡：局部廊道绿化能够改变微气候结构，但无法完全抵消不透水面扩张所导致的全城增温效应。将热舒适度指标和最低植被覆盖率纳入空间规划，对于建设气候适应性城市至关重要。",null,"City and Environment Interactions","2026-09-06T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"主题为城市热岛效应与城市更新，不涉及三农、农业信息化或智慧农业，不符合相关性门槛。",[19],{"name":10,"url":6},[21],"城市热岛",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":30,"locked":14,"version":31,"method":32,"evidence":33},"classified","2026-10-22.2","rules",{"candidates":34,"agricultural_evidence":37},[35,43],{"code":23,"score":36,"supported":37,"title":38,"abstract":40,"tags":42},14,true,[39],"machine learning",[41,39],"机器学习",[],{"code":44,"score":45,"supported":37,"title":46,"abstract":47,"tags":49},"H7",3,[],[48],"气候适应",[],[],"Evaluatingthethermalimpactsofurbancorrid-2004",2,"10.1016\u002Fj.cacint.2026.100465",{"doi":53,"openalex_id":55,"authors":56,"venue":10,"cited_by_count":15,"oa_url":70,"card":71,"direction":77,"ingested_from":78},"W7210262114",[57,60,63,65,67],{"name":58,"orcid":59},"Talema Moged Reda","https:\u002F\u002Forcid.org\u002F0000-0002-4320-7277",{"name":61,"orcid":62},"Ashenif Melese Abraham","https:\u002F\u002Forcid.org\u002F0000-0001-7154-9576",{"name":64,"orcid":9},"Wondimu Haimanote",{"name":66,"orcid":9},"Zerihun Chere",{"name":68,"orcid":69},"Bireda Alemayehu","https:\u002F\u002Forcid.org\u002F0009-0005-0187-920X","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2590252026001728\u002Fpdf",{"tldr":72,"method":73,"finding":74,"direction":75,"opportunity":76},"评估亚的斯亚贝巴走廊改造与绿化对地表温度的影响，发现建成区扩张导致升温5.06°C，绿化无法抵消。","利用Landsat多时相影像，随机森林分类，结合NDVI、NDBI和UTFVI分","建成区从14.8%增至53.3%，平均地表温度上升5.06°C，SUHI强度增强，绿化仅局部降温。","其他","可延伸研究城市绿化与不透水面扩张的权衡，探索最小绿化覆盖率阈值以缓解热岛效应。","农业遥感与作物表型","openalex","2026-09-09T23:30:25.219136Z",{"total":81,"page":82,"page_size":81,"items":83},6,1,[84,171,237,304,356,407],{"id":85,"title":86,"url":87,"summary":88,"summary_zh":89,"content":9,"source_name":90,"source_url":87,"published_at":91,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":92,"score_detail":93,"sources":100,"tags":102,"primary_topic":105,"secondary_topics":106,"classification":107,"search_phrases":138,"slug":141,"view_count":116,"doi":142,"paper":143,"created_at":170},4171,"A machine learning framework for predicting potential urban cool island locations using Landsat 9 data: a case study of Oued Zenati, Algeria","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-72875-3","Abstract Urban heat stress is increasing in semi-arid Mediterranean towns, making the identification of Urban Cool Island (UCI) patterns essential for climate-resilient urban planning. This study developed an integrated remote sensing, GIS, and explainable machine-learning framework to map potential UCI locations in Oued Zenati, northeastern Algeria, using Landsat 9 imagery and geospatial environmental variables processed in Google Earth Engine. ArcGIS Desktop 10.8 was used for the final cartographic layout and map generation. Predictor variables included land surface temperature, albedo, elevation, slope, distance to roads, distance to rivers, and population density. Because field observations of UCIs were unavailable, proxy reference samples were generated from vegetation, moisture, and built-up indicators. Under the prevailing semi-arid conditions, NDWI values remained below − 0.06 across the study area, and all cool-zone reference samples were therefore derived from the vegetation criterion (NDVI ≥ 0.20). Four machine-learning algorithms (Random Forest, Gradient Tree Boosting, CART, and MaxEnt) were evaluated using a 70\u002F30 training-testing split and independent validation. Gradient Tree Boosting achieved the highest discrimination ability (ROC-AUC = 0.916), whereas Random Forest provided the best threshold-dependent performance, with an accuracy of 0.900, Kappa of 0.800, Precision of 0.929, and F1-score of 0.897. Susceptibility maps showed that cooling potential is concentrated in vegetated and agricultural areas, while built-up and bare surfaces exhibit low cooling potential. SHAP analysis identified elevation as the most influential predictor, followed by slope, albedo, and land surface temperature, whereas distance to roads, distance to rivers, and population density exerted comparatively weaker effects. The proposed framework provides a robust, interpretable, and transferable approach for Urban Cool Island susceptibility mapping, supporting climate adaptation, green infrastructure planning, and sustainable urban development in semi-arid cities.","摘要 在半干旱地中海城镇，城市热胁迫日益加剧，因此识别城市冷岛（Urban Cool Island, UCI）格局对于气候适应性城市规划至关重要。本研究开发了一个集成遥感、GIS和可解释机器学习的框架，利用Landsat 9影像和在Google Earth Engine中处理的地理空间环境变量，绘制了阿尔及利亚东北部Oued Zenati潜在UCI位置图。使用ArcGIS Desktop 10.8进行最终制图布局和地图生成。预测变量包括地表温度、反照率、高程、坡度、距道路距离、距河流距离和人口密度。由于缺乏UCI的实地观测数据，研究从植被、湿度和建成区指标生成了代理参考样本。在半干旱条件下，研究区NDWI值均低于−0.06，因此所有冷区参考样本均基于植被标准（NDVI ≥ 0.20）提取。采用70\u002F30的训练-测试划分和独立验证，评估了四种机器学习算法（随机森林、梯度树提升、CART和MaxEnt）。梯度树提升取得了最高的判别能力（ROC-AUC = 0.916），而随机森林在阈值依赖性能方面表现最佳，准确率为0.900，Kappa为0.800，精确率为0.929，F1分数为0.897。敏感性图显示，降温潜力集中在植被和农业区域，而建成区和裸地表面的降温潜力较低。SHAP分析表明，高程是最具影响力的预测变量，其次是坡度、反照率和地表温度，而距道路距离、距河流距离和人口密度的影响相对较弱。所提出的框架为城市冷岛敏感性制图提供了一种稳健、可解释且可迁移的方法，可支持半干旱城市的气候适应、绿色基础设施规划和可持续城市发展。","Scientific Reports","2026-10-03T00:00:00Z",66,{"impact":94,"substance":95,"depth":96,"authority":97,"freshness":98,"relevant":82,"comment":99},8,20,16,13,9,"方法新颖、结论可靠的城市冷岛遥感预测研究，对农业信息化与气候适应型规划有参考价值，但属区域案例、影响范围有限。",[101],{"name":90,"url":87},[103,41,104,48,21],"智慧农业","遥感",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},[],{"status":30,"locked":14,"version":31,"method":32,"evidence":108},{"candidates":109,"agricultural_evidence":37},[110,115,121,127,133],{"code":23,"score":111,"supported":37,"title":112,"abstract":113,"tags":114},12,[39],[41],[41],{"code":44,"score":116,"supported":37,"title":117,"abstract":118,"tags":120},7,[],[48,119],"干旱",[48],{"code":122,"score":116,"supported":37,"title":123,"abstract":124,"tags":126},"I3",[],[104,125],"remote sensing",[104],{"code":128,"score":45,"supported":37,"title":129,"abstract":130,"tags":132},"I4",[],[131],"GIS",[],{"code":134,"score":82,"supported":14,"title":135,"abstract":136,"tags":137},"I1",[],[],[103],[139,140],"Landsat 9 城市冷岛 阿尔及利亚","Oued Zenati 城市冷岛 遥感","Landsat9城市冷岛阿尔及利亚-4171","10.1038\u002Fs41598-026-72875-3",{"doi":142,"openalex_id":144,"authors":145,"venue":90,"cited_by_count":15,"oa_url":87,"card":165,"direction":77,"ingested_from":78},"W7218855599",[146,148,150,153,156,159,162],{"name":147,"orcid":9},"Amina Naidja",{"name":149,"orcid":9},"Dalal FARID",{"name":151,"orcid":152},"Djamal Bengusmia","https:\u002F\u002Forcid.org\u002F0000-0003-4480-8637",{"name":154,"orcid":155},"Haythem Dinar","https:\u002F\u002Forcid.org\u002F0000-0002-4504-2963",{"name":157,"orcid":158},"Nouh Rebouh","https:\u002F\u002Forcid.org\u002F0000-0001-6214-2942",{"name":160,"orcid":161},"Imtiyaz Akbar Najar","https:\u002F\u002Forcid.org\u002F0000-0002-7338-6771",{"name":163,"orcid":164},"Nadeem Ahmad Khan","https:\u002F\u002Forcid.org\u002F0000-0003-4366-9639",{"tldr":166,"method":167,"finding":168,"direction":77,"opportunity":169},"用遥感与可解释机器学习预测阿尔及利亚半干旱城市潜在城市冷岛位置。","Landsat 9、Google Earth Engine、GIS与四种机器学习","梯度提升树判别最优（AUC=0.916），冷岛潜力集中于植被与农业区，海拔为最关键预测因子。","可迁移至其他半干旱城市，并引入时序遥感与实地冷岛观测验证，提升模型泛化性。","2026-10-04T23:30:24.545092Z",{"id":172,"title":173,"url":174,"summary":175,"summary_zh":176,"content":9,"source_name":177,"source_url":174,"published_at":178,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":179,"score_detail":180,"sources":184,"tags":186,"primary_topic":191,"secondary_topics":197,"classification":199,"search_phrases":216,"slug":219,"view_count":15,"doi":220,"paper":221,"created_at":236},5592,"Evaluation of Concept-Rank Collapse Audits for Computer Vision Agriculture Disease Classifiers Under Low-Label Regimes: An Interpretability Capacity Bound for Smallholder Fungicide Selectivity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545193","Concept-based interpretability methods for plant-disease classifiers are typically evaluated by whether their concept activations correlate with human-annotated labels, but this criterion is silent on a prior question: whether the classifier's internal representation retains enough concept-rank structure for any audit to be informative. the present analysis formalises that prior question as an interpretability capacity bound. A classifier is modelled as a concept-rank operator whose singular values govern how much concept-level signal survives the projection from pixel space to class logits, and a collapse audit is defined as the ratio of retained concept-rank energy to total concept energy. Under a low-label regime, where concept annotations are scarce and the audit must be estimated from few labelled examples, the bound predicts that audit reliability degrades as a function of the concept-rank spectrum and the label budget. The analysis is a theoretical and methodological contribution: it derives the bound, states the conditions under which a collapse audit is identifiable, and characterises the operating characteristics of the audit as a decision procedure under a declared variance structure (between-cluster SD = 6.0, residual SD = 4.5, intraclass correlation = 0.64). Power was estimated across 2000 design cells for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points; 52 clusters were required for 5 percentage points at 80% power. The bound reframes concept audits as capacity tests rather than fidelity tests, with consequences for how smallholder fungicide-selectivity decisions should be supported by interpretable disease classifiers.","面向植物病害分类器的基于概念的可解释性方法，通常以其概念激活是否与人工标注标签相关作为评价标准，但该标准对一个更先前的问题保持沉默：分类器的内部表征是否保留了足够的概念秩结构，从而使任何审计具有信息量。本分析将该先前问题形式化为一个可解释性容量上界。分类器被建模为概念秩算子，其奇异值支配着从像素空间到类别logits的投影中概念级信号得以保留的程度，并将坍缩审计定义为保留的概念秩能量与总概念能量之比。在低标签情形下，概念标注稀缺且审计必须由少量标注样本估计，该上界预测审计可靠性会随概念秩谱和标签预算的函数而退化。本分析是一项理论和方法论贡献：推导出该上界，陈述坍缩审计可识别的条件，并在声明的方差结构（簇间SD = 6.0，残差SD = 4.5，组内相关系数 = 0.64）下刻画审计作为决策程序的操作特征。在2000个设计单元中，针对簇数为8、16、24和32以及效应量为3、5和8个百分点的情形估计了功效；在80%功效下达到5个百分点需要52个簇。该上界将概念审计重新框定为容量检验而非保真度检验，并对可解释病害分类器应如何支持小农杀菌剂选择性决策具有启示意义。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",69,{"impact":94,"substance":181,"depth":182,"authority":111,"freshness":13,"relevant":82,"comment":183},21,18,"理论方法论文，提出可解释性容量上界并给出审计功效分析，对智慧农业病害识别可信度有参考价值，但属小众方法学研究、缺乏田间实证，暂不宜进入每日精选。",[185],{"name":177,"url":174},[103,187,188,189,190],"农业人工智能","小农户","植物病害识别","可解释性",{"code":192,"slug":193,"name":194,"path":195,"parent_code":196},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[198],{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},{"status":30,"locked":14,"version":31,"method":32,"evidence":200},{"candidates":201,"agricultural_evidence":37},[202,207,212],{"code":192,"score":111,"supported":37,"title":203,"abstract":205,"tags":206},[204],"smallholder",[204],[188],{"code":23,"score":13,"supported":37,"title":208,"abstract":210,"tags":211},[209],"computer vision",[],[187,189],{"code":134,"score":82,"supported":14,"title":213,"abstract":214,"tags":215},[],[],[103],[217,218],"农业人工智能 植物病害识别 可解释性 智慧农业","农业人工智能 植物病害识别","农业人工智能植物病害识别可解释性智慧农业-5592","10.5281\u002Fzenodo.23545193",{"doi":220,"openalex_id":222,"authors":223,"venue":177,"cited_by_count":15,"oa_url":174,"card":230,"direction":234,"ingested_from":78},"W7223137323",[224,226,228],{"name":225,"orcid":9},"Akshay Ramgoolam",{"name":227,"orcid":9},"Priya Bundhoo Appadoo",{"name":229,"orcid":9},"Jean-Noël LEspérance",{"tldr":231,"method":232,"finding":233,"direction":234,"opportunity":235},"提出可解释性容量上界，评估低标签下概念秩崩溃审计的可靠性。","将分类器建模为概念秩算子，推导容量上界并做2000格功效模拟。","审计可靠性随概念秩谱与标签预算下降；5个百分点效应需52个聚类达80%功效。","农业人工智能与决策模型","可将容量上界用于小农户杀菌剂选择性决策的可解释模型审计与标签预算设计。","2026-10-22T11:21:10.425290Z",{"id":238,"title":239,"url":240,"summary":241,"summary_zh":242,"content":9,"source_name":177,"source_url":240,"published_at":178,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":179,"score_detail":243,"sources":246,"tags":248,"primary_topic":252,"secondary_topics":258,"classification":260,"search_phrases":286,"slug":289,"view_count":15,"doi":290,"paper":291,"created_at":303},5591,"Hierarchical Conformal Risk Control for Artificial Intelligence Agriculture Irrigation Scheduling Under Unmodeled Infiltration: A Computer Safety-Guarantee Evaluation","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23543665","Irrigation scheduling algorithms that rely on soil-moisture forecasts are vulnerable to unmodeled infiltration, the process by which water bypasses the root zone through preferential pathways that resistance-based soil models cannot represent. The framework is evaluated through a replication-based design study that characterises the operating characteristics of the before-after-control-impact estimator used to audit scheduler performance, under a declared variance structure with between-cluster standard deviation 6.0, residual standard deviation 4.5 and intraclass correlation 0.64. Power was estimated across 2000 design cells spanning cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. The analysis indicates that 54 clusters are required to detect a 5-percentage-point effect at 80% power, and that the minimum detectable effect declines steeply as cluster count rises from 8 to 32. The contribution is a formal safety guarantee for irrigation decision support that remains valid when the infiltration model is wrong, together with an audit design that makes the guarantee empirically checkable.","依赖土壤湿度预报的灌溉调度算法容易受到未建模入渗的影响，即水分通过优先路径绕过根区的过程，而基于阻力的土壤模型无法表征这一过程。该框架通过一项基于重复的设计研究进行评估，该研究刻画了用于审计调度器性能的前后对照影响估计量的运行特性，其所依据的声明方差结构为：组间标准差6.0、残差标准差4.5、组内相关系数0.64。功效估计覆盖2000个设计单元，涵盖聚类数8、16、24和32以及效应量3、5和8个百分点。分析表明，在80%功效下检测5个百分点效应需要54个聚类，且最小可检测效应随聚类数从8增至32而急剧下降。本文的贡献在于为灌溉决策支持提供了一种正式的安全保证，该保证在入渗模型错误时仍然有效，同时提出了一种使该保证可经实证检验的审计设计。",{"impact":94,"substance":244,"depth":182,"authority":111,"freshness":98,"relevant":82,"comment":245},22,"该研究提出在入渗模型失配条件下仍有效的灌溉决策安全保证框架，并给出可审计的试验设计，方法新颖、结论可靠，但属细分方法学研究，产业影响有限，适合作为专业精选而非头条。",[247],{"name":177,"url":240},[103,187,249,250,251],"灌溉决策","安全保证","试验设计",{"code":253,"slug":254,"name":255,"path":256,"parent_code":257},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[259],{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},{"status":30,"locked":14,"version":31,"method":32,"evidence":261},{"candidates":262,"agricultural_evidence":37},[263,269,275,282],{"code":253,"score":264,"supported":37,"title":265,"abstract":266,"tags":268},15,[254],[267,254],"灌溉",[249],{"code":23,"score":111,"supported":37,"title":270,"abstract":272,"tags":274},[271],"artificial intelligence",[273],"decision support",[187],{"code":276,"score":81,"supported":37,"title":277,"abstract":278,"tags":281},"H2",[],[279,280],"土壤","soil",[],{"code":134,"score":82,"supported":14,"title":283,"abstract":284,"tags":285},[],[],[103],[287,288],"灌溉调度 安全保证","农业人工智能 安全保证 智慧农业 灌溉决策","灌溉调度安全保证-5591","10.5281\u002Fzenodo.23543665",{"doi":290,"openalex_id":292,"authors":293,"venue":177,"cited_by_count":15,"oa_url":240,"card":298,"direction":234,"ingested_from":78},"W7223131205",[294,296],{"name":295,"orcid":9},"Nassima Benkhelifa",{"name":297,"orcid":9},"Yacine Aït Ahmed",{"tldr":299,"method":300,"finding":301,"direction":234,"opportunity":302},"提出分层保形风险控制，为未建模入渗下的灌溉调度提供安全保证。","分层保形风险控制与基于重复设计的BACI审计，2000个设计单元功效分析。","检测5个百分点效应需54个集群，最小可检测效应随集群数增加陡降。","可将保形风险控制扩展到其他未建模扰动下的农业决策安全保证与审计设计。","2026-10-22T11:21:10.283561Z",{"id":305,"title":306,"url":307,"summary":308,"summary_zh":309,"content":9,"source_name":177,"source_url":307,"published_at":178,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":310,"score_detail":311,"sources":313,"tags":315,"primary_topic":318,"secondary_topics":319,"classification":321,"search_phrases":336,"slug":339,"view_count":15,"doi":340,"paper":341,"created_at":355},5590,"Evaluation of Concept-Probe Temporal-Stability Audits for Computer Vision Agriculture Disease Classifiers Under Seasonal Phenology Drift: An Interpretability Decay Bound for Smallholder Fungicide Timing","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545234","Concept-probe audits are increasingly used to certify that a crop-disease classifier's internal representations track the pathological concepts a smallholder would act on, but a probe certified at one point in the season may silently decouple from those concepts as phenology shifts the visual statistics of the field. the present analysis treats that decoupling as a formal object. It defines a temporal-stability audit as a sequence of concept-probe accuracies measured across defined phenological windows, and it derives an interpretability decay bound: the rate at which probe accuracy can fall before the fungicide-timing decision it is meant to support becomes unreliable. The bound is expressed as a function of the probe's initial margin, the drift in concept prevalence between windows, and the classifier's sensitivity to the drifted features, and it yields a certified audit interval rather than a single-point certificate. The paper then characterises the operating characteristics of the audit design under a declared variance structure, using a replication-based evaluation of the before-after-control-impact estimator with between-cluster SD = 6.0, residual SD = 4.5 and intraclass correlation = 0.64. Power was estimated across 2000 design cells over cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points; 54 clusters were required for 5 percentage points at 80% power. The contribution is a decision-theoretic account of when a concept-probe certificate expires, and a design rule for scheduling re-audits across the season.","概念探针审计（concept-probe audit）日益被用于验证作物病害分类器的内部表征是否追踪小农户会据以采取行动的病理学概念，但在生长季某一时点获得认证的探针，可能随着物候变化改变田间的视觉统计特征而悄然与这些概念脱钩。本分析将这种脱钩视为一个形式化对象。它将时间稳定性审计（temporal-stability audit）定义为在既定物候窗口内测量的一系列概念探针准确率，并推导出一个可解释性衰减界限（interpretability decay bound）：即探针准确率在其所支持的杀菌剂施用时机决策变得不可靠之前所能下降的速率。该界限表示为探针初始裕度、窗口间概念流行率漂移以及分类器对漂移特征敏感度的函数，并给出一个经认证的审计区间而非单点认证。随后，本文在声明的方差结构下刻画该审计设计的运行特征，采用基于重复的前后对照影响估计量评估，其中组间标准差 = 6.0、残差标准差 = 4.5、组内相关系数 = 0.64。功效在 2000 个设计单元上估计，聚类数取 8、16、24 和 32，效应量取 3、5 和 8 个百分点；在 80% 功效下达到 5 个百分点需要 54 个聚类。本文的贡献在于从决策论角度阐明概念探针认证何时失效，并给出在整个生长季内安排重新审计的设计规则。",70,{"impact":94,"substance":244,"depth":182,"authority":111,"freshness":13,"relevant":82,"comment":312},"该论文提出概念探针审计的时序稳定性框架与可解释性衰减界，方法新颖、统计设计扎实，但属小众方法论研究，产业影响有限，适合作为专业精选而非头条。",[314],{"name":177,"url":307},[103,187,188,316,317],"作物病害识别","模型审计",{"code":192,"slug":193,"name":194,"path":195,"parent_code":196},[320],{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},{"status":30,"locked":14,"version":31,"method":32,"evidence":322},{"candidates":323,"agricultural_evidence":37},[324,328,332],{"code":192,"score":264,"supported":37,"title":325,"abstract":326,"tags":327},[204],[188,204],[188],{"code":23,"score":13,"supported":37,"title":329,"abstract":330,"tags":331},[209],[],[316,187],{"code":134,"score":82,"supported":14,"title":333,"abstract":334,"tags":335},[],[],[103],[337,338],"概念探针 时序稳定性 作物病害分类器","杀菌剂 施药时机 可解释性衰减","概念探针时序稳定性作物病害分类器-5590","10.5281\u002Fzenodo.23545234",{"doi":340,"openalex_id":342,"authors":343,"venue":177,"cited_by_count":15,"oa_url":307,"card":350,"direction":234,"ingested_from":78},"W7223088030",[344,346,348],{"name":345,"orcid":9},"Abdi-Basid Idriss Farah",{"name":347,"orcid":9},"Amina Abdillahi Guedi",{"name":349,"orcid":9},"Moussa Omar Youssouf",{"tldr":351,"method":352,"finding":353,"direction":234,"opportunity":354},"提出概念探针时间稳定性审计与可解释性衰减界，判断何时需重新审计。","定义跨物候窗口探针精度序列，推导衰减界，用BACI复制评估统计功效。","5个百分点效应需54个聚类达80%功效，审计证书会随物候漂移过期。","可将衰减界与再审计调度规则嵌入小农户杀菌剂时机决策支持系统，并验证跨作物泛化。","2026-10-22T11:21:08.978348Z",{"id":357,"title":358,"url":359,"summary":360,"summary_zh":361,"content":9,"source_name":177,"source_url":359,"published_at":178,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":362,"score_detail":363,"sources":366,"tags":368,"primary_topic":371,"secondary_topics":372,"classification":373,"search_phrases":391,"slug":394,"view_count":15,"doi":395,"paper":396,"created_at":406},5589,"Conformal-Risk Evaluation for Artificial Intelligence Agriculture Spray-Nozzle Fault Detection Under Label-Delay Feedback: A Computer Coverage Audit","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23544107","Spray-nozzle fault detection in precision agriculture is a classification problem in which the label that confirms a fault arrives after the spray pass, so the detector must act on unlabelled evidence and its error rate must be certified before the label exists. Conformal prediction offers distribution-free coverage guarantees, but the guarantee is stated for exchangeable calibration and test data, an assumption that label-delayed feedback violates because the calibration set is always older than the deployment set. the present analysis formalises label-delay feedback as a distribution shift in the conformity score and derives a coverage bound for split-conformal fault detectors under that shift. The bound separates the nominal miscoverage rate into an exchangeable component and a delay-induced component that scales with the total variation distance between the calibration and deployment score distributions. A replication-based evaluation of the ['Intercept', 'exposure', 'group', 'severity'] estimator was conducted: 600 data sets of N = 500 were drawn from a declared data-generating process (intercept 12.0, exposure 0.42, group -3.1, severity 1.35, error SD 4.2), and the study characterises the behaviour of the ordinary least squares estimator under the stated process. The estimator recovered the declared coefficients with estimated bias 0.01122 for the intercept and -0.0002 for exposure, root mean squared error 0.9217 and 0.01614 respectively, and empirical coverage of the nominal 95% intervals of 1.0 for both parameters across 600 replications. The coverage audit shows that the delay-induced term, not the exchangeable term, dominates the risk of a conformal spray-nozzle detector, and that the audit procedure can certify a detector before field labels return.","在精准农业中，喷雾喷嘴故障检测是一个分类问题，其中确认故障的标签在喷雾作业结束后才到达，因此检测器必须基于未标记的证据采取行动，并且其错误率必须在标签存在之前得到认证。保形预测（conformal prediction）提供了无分布覆盖保证，但该保证是针对可交换的校准数据和测试数据而言的，而标签延迟反馈违反了这一假设，因为校准集总是比部署集更旧。本分析将标签延迟反馈形式化为一致性分数中的分布偏移，并推导了在该偏移下分裂保形故障检测器的覆盖界。该界将名义错误覆盖 rate 分解为可交换分量和延迟诱导分量，后者随校准与部署分数分布之间的全变差距离而缩放。对 ['Intercept', 'exposure', 'group', 'severity'] 估计器进行了基于重复的评估：从声明的数据生成过程（截距 12.0，暴露 0.42，分组 -3.1，严重程度 1.35，误差标准差 4.2）中抽取了 600 个 N = 500 的数据集，研究刻画了普通最小二乘估计器在所述过程下的行为。该估计器恢复了声明的系数，截距的估计偏差为 0.01122，暴露为 -0.0002，均方根误差分别为 0.9217 和 0.01614，两个参数在 600 次重复中名义 95% 区间的经验覆盖率为 1.0。覆盖审计表明，延迟诱导项而非可交换项主导了保形喷雾喷嘴检测器的风险，并且该审计程序可以在田间标签返回之前对检测器进行认证。",62,{"impact":94,"substance":182,"depth":364,"authority":98,"freshness":13,"relevant":82,"comment":365},17,"论文提出标签延迟下共形预测覆盖界，方法有新意但属预印本、应用面窄，可作为专业补充而非每日精选头条。",[367],{"name":177,"url":359},[103,187,369,370],"精准施药","病虫害监测",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},[],{"status":30,"locked":14,"version":31,"method":32,"evidence":374},{"candidates":375,"agricultural_evidence":37},[376,380,386],{"code":23,"score":98,"supported":37,"title":377,"abstract":378,"tags":379},[271],[],[187],{"code":134,"score":116,"supported":37,"title":381,"abstract":382,"tags":385},[],[383,384],"精准农业","precision agriculture",[103],{"code":387,"score":82,"supported":14,"title":388,"abstract":389,"tags":390},"F4",[],[],[369],[392,393],"农业人工智能 病虫害监测 智慧农业 精准施药","农业人工智能 病虫害监测","农业人工智能病虫害监测智慧农业精准施药-5589","10.5281\u002Fzenodo.23544107",{"doi":395,"openalex_id":397,"authors":398,"venue":177,"cited_by_count":15,"oa_url":359,"card":401,"direction":234,"ingested_from":78},"W7223116087",[399],{"name":400,"orcid":9},"Achieng' Atim Okello",{"tldr":402,"method":403,"finding":404,"direction":234,"opportunity":405},"将标签延迟反馈建模为共形分数分布偏移，推导覆盖率界并审计喷雾喷嘴故障检测器。","分裂共形预测、总变差距离、600次重复模拟（N=500）评估OLS估计。","延迟诱导项而非可交换项主导检测器风险，审计可在田间标签返回前认证检测器。","可将该覆盖率审计框架扩展到其他标签延迟的农业传感器故障检测，并研究延迟分布估计误差对认证的影响。","2026-10-22T11:21:02.845718Z",{"id":408,"title":409,"url":410,"summary":411,"summary_zh":412,"content":9,"source_name":177,"source_url":410,"published_at":178,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":413,"score_detail":414,"sources":416,"tags":418,"primary_topic":421,"secondary_topics":422,"classification":423,"search_phrases":449,"slug":452,"view_count":15,"doi":453,"paper":454,"created_at":464},5588,"Certified Temporal Fusion of Artificial Intelligence Climate Analytics for Crop Failure Early Warning Under Sparse Agricultural Sensors: Error Bounds and Famine Relief Targeting","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545489","Sparse agricultural sensor networks across sub-Saharan Africa leave crop-failure early-warning systems with too little ground observation to support reliable famine relief targeting. The framework treats sensor sparsity as a missing-data problem with a known observation operator and propagates climate-analytics uncertainty through a temporal Kalman-Buys filter whose gain is constrained by a certified risk envelope. Using NASA POWER monthly reanalysis for Accra, Ghana (2000-2023, 312 observations), the analysis establishes a mean temperature of 26.521 C and a warming trend of 0.1622 C per decade, which calibrates the climate-analytics prior. The derived bounds show that relief-targeting error scales with the square root of sensor density and with the Lipschitz constant of the crop-response function, yielding an explicit sensor-placement rule for a target misclassification rate. The contribution is a certified, assumption-explicit bridge between climate analytics and famine relief targeting that states the conditions under which early warning is trustworthy.","撒哈拉以南非洲稀疏的农业传感器网络使得作物歉收预警系统缺乏足够的地面观测数据，难以支撑可靠的饥荒救援目标定位。该框架将传感器稀疏性视为具有已知观测算子的缺失数据问题，并通过时间Kalman-Buys滤波器传播气候分析不确定性，该滤波器的增益受经认证的风险包络约束。利用NASA POWER对加纳阿克拉的月度再分析数据（2000—2023年，312个观测值），分析确定了平均气温为26.521°C、每十年0.1622°C的增暖趋势，据此校准了气候分析先验。推导出的界限表明，救援目标定位误差随传感器密度的平方根以及作物响应函数的Lipschitz常数缩放，从而为目标误分类率给出了明确的传感器布设规则。该研究的贡献在于构建了一个经认证的、假设明确的气候分析与饥荒救援目标定位之间的桥梁，阐明了早期预警可信赖的条件。",74,{"impact":111,"substance":244,"depth":182,"authority":111,"freshness":13,"relevant":82,"comment":415},"该研究提出一种带误差界认证的时序融合方法，用于稀疏传感器条件下的作物歉收预警与饥荒救援瞄准，方法新颖、结论明确，但案例局限于加纳阿克拉，产业影响有限，适合作为技术前沿条目收录。",[417],{"name":177,"url":410},[103,187,419,104,420],"粮食安全","气候分析",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},[],{"status":30,"locked":14,"version":31,"method":32,"evidence":424},{"candidates":425,"agricultural_evidence":37},[426,430,436,441,445],{"code":23,"score":98,"supported":37,"title":427,"abstract":428,"tags":429},[271],[],[187],{"code":431,"score":45,"supported":37,"title":432,"abstract":433,"tags":435},"I5",[],[434],"农业传感",[],{"code":437,"score":82,"supported":14,"title":438,"abstract":439,"tags":440},"A8",[],[],[419],{"code":134,"score":82,"supported":14,"title":442,"abstract":443,"tags":444},[],[],[103],{"code":122,"score":82,"supported":14,"title":446,"abstract":447,"tags":448},[],[],[104],[450,451],"NASA POWER 加纳 气候分析","作物歉收 早期预警 传感器","NASAPOWER加纳气候分析-5588","10.5281\u002Fzenodo.23545489",{"doi":453,"openalex_id":455,"authors":456,"venue":177,"cited_by_count":15,"oa_url":410,"card":459,"direction":234,"ingested_from":78},"W7223111766",[457],{"name":458,"orcid":9},"Fatima-Zahra El Khattabi",{"tldr":460,"method":461,"finding":462,"direction":77,"opportunity":463},"提出带误差界的时间融合框架，在稀疏传感器下用气候分析预警作物歉收。","卡尔曼-布西滤波+NASA POWER再分析数据，风险包络约束增益。","救济瞄准误差随传感器密度平方根和作物响应Lipschitz常数缩放，给出布点规则。","可将该认证误差界框架扩展到多作物多区域，结合卫星遥感弥补地面传感器稀疏。","2026-10-22T11:21:02.682497Z"]