{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":4,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":4,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"16e79d5a7892","filters":{"venue":"Journal of Remote Sensing"}},"results":[{"id":"W4313560427","doi":"10.34133/remotesensing.0005","title":"Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019","year":2023,"lang":"en","type":"article","venue":"Journal of Remote Sensing","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Remote sensing; Microwave; Environmental science; China; Computer science; Geography; Telecommunications","authors":[{"name":"Zhongbing Chang","is_ca":false},{"name":"Lei Fan","is_ca":false},{"name":"Jean‐Pierre Wigneron","is_ca":false},{"name":"Ying‐Ping Wang","is_ca":false},{"name":"Philippe Ciais","is_ca":false},{"name":"Jérôme Chave","is_ca":false},{"name":"Rasmus Fensholt","is_ca":false},{"name":"Jing M. Chen","is_ca":true},{"name":"Wenping Yuan","is_ca":false},{"name":"Weimin Ju","is_ca":false},{"name":"Xin Li","is_ca":false},{"name":"Fei Jiang","is_ca":false},{"name":"Mousong Wu","is_ca":false},{"name":"Xiuzhi Chen","is_ca":false},{"name":"Yuanwei Qin","is_ca":false},{"name":"Frédéric Frappart","is_ca":false},{"name":"Xiaojun Li","is_ca":false},{"name":"Mengjia Wang","is_ca":false},{"name":"Xiangzhuo Liu","is_ca":false},{"name":"Xuli Tang","is_ca":false},{"name":"Sanaa Hobeichi","is_ca":false},{"name":"Mengxiao Yu","is_ca":false},{"name":"Mingguo Ma","is_ca":false},{"name":"Jianguang Wen","is_ca":false},{"name":"Qing Xiao","is_ca":false},{"name":"Weiyu Shi","is_ca":false},{"name":"Dexin Liu","is_ca":false},{"name":"Junhua Yan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009275287548129289,"gpt":0.2411807147745021,"spread":0.2319054272263729,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006740145,0.000665676,0.0002929611,0.001355087,0.0002447601,0.0004408014,0.0004627337,0.0003265718,0.0003420095],"category_scores_gemma":[0.0006635342,0.0002272504,0.0006065767,0.001478235,0.0001850033,0.0004909421,0.0003837695,0.0001632616,0.0001173514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001333364,"about_ca_system_score_gemma":0.0009247604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1312018,"about_ca_topic_score_gemma":0.125416,"domain_scores_codex":[0.9998357,0.00001721603,0.0000153359,0.00006088497,0.0000355765,0.00003528352],"domain_scores_gemma":[0.9997142,0.00003709954,0.00005944262,0.00003401038,0.0001200712,0.00003508402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001158773,0.00007523382,0.9166857,0.00008266208,0.0002593257,0.0002794988,0.0001642318,0.04550143,0.005909213,0.0002615222,0.001532421,0.02913293],"study_design_scores_gemma":[0.000009401379,0.00001959582,0.9148445,0.00001183738,0.00007183654,0.00003574732,0.00009671403,0.08246364,0.001329686,0.00009677271,0.001001081,0.00001927052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952118,0.0001344359,0.0009758755,0.00005674943,0.000006458877,0.0000112738,0.003054552,0.00006927656,0.0004797423],"genre_scores_gemma":[0.9932493,0.00009192564,0.001113717,0.00002182732,0.000006813658,0.00001415785,0.005282998,0.000006878169,0.000212465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1312018,"threshold_uncertainty_score":0.2608762,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3201254861","doi":"10.34133/2021/9795837","title":"Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products","year":2021,"lang":"en","type":"article","venue":"Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; China Postdoctoral Science Foundation; National Natural Science Foundation of China; California Institute of Technology","keywords":"Algorithm; Geology; Computer science","authors":[{"name":"Zhaoying Zhang","is_ca":false},{"name":"Yongguang Zhang","is_ca":false},{"name":"Jing M. Chen","is_ca":true},{"name":"Weimin Ju","is_ca":false},{"name":"Mirco Migliavacca","is_ca":false},{"name":"Tarek S. El‐Madany","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01287262635440394,"gpt":0.2395092312066877,"spread":0.2266366048522837,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001827763,0.0005756755,0.0003348023,0.0006987936,0.0001595517,0.0009938717,0.0004079778,0.0006221143,0.001080535],"category_scores_gemma":[0.005484541,0.0003677967,0.000539911,0.0003747043,0.0001320226,0.0008994635,0.0004297196,0.0003794556,0.000566641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004943004,"about_ca_system_score_gemma":0.0001804434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01237213,"about_ca_topic_score_gemma":0.006823619,"domain_scores_codex":[0.9993241,0.0001521362,0.00002968446,0.0002482403,0.0001633831,0.00008257662],"domain_scores_gemma":[0.9978313,0.001487306,0.0001102385,0.0002022537,0.0003278115,0.00004102384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001297077,0.0001987046,0.4499623,0.0003049086,0.001019099,0.0004722672,0.0003196814,0.3791922,0.0697496,0.0006539773,0.002806628,0.09402351],"study_design_scores_gemma":[0.00003107724,0.0001157126,0.5274086,0.00006755249,0.0001272739,0.0002716854,0.0001544601,0.4409537,0.02757189,0.0006610114,0.002543965,0.00009303282],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9691651,0.0006429417,0.02241507,0.00008395218,0.00002447079,0.00003527691,0.00278263,0.001053825,0.00379664],"genre_scores_gemma":[0.9889024,0.0001445771,0.006905659,0.00006122855,0.000006117324,0.00001452891,0.003285911,0.000102884,0.0005766021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01237213,"threshold_uncertainty_score":0.02460027,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205804353","doi":"10.34133/2022/9816536","title":"Global Terrestrial Ecosystem Carbon Flux Inferred from TanSat XCO <sub>2</sub> Retrievals","year":2022,"lang":"en","type":"article","venue":"Journal of Remote Sensing","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Nanjing University; National Oceanic and Atmospheric Administration; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Environmental science; Latitude; Temperate climate; Carbon sink; Tropics; Carbon cycle; Atmospheric sciences; Climatology; Ecosystem; Terrestrial ecosystem; Carbon flux; Greenhouse gas; Northern Hemisphere; Physical geography; Geography; Geology; Oceanography; Ecology","authors":[{"name":"Hengmao Wang","is_ca":false},{"name":"Fei Jiang","is_ca":false},{"name":"Yi Liu","is_ca":false},{"name":"Dongxu Yang","is_ca":false},{"name":"Mousong Wu","is_ca":false},{"name":"Wei He","is_ca":false},{"name":"Jun Wang","is_ca":false},{"name":"Jing Wang","is_ca":false},{"name":"Weimin Ju","is_ca":false},{"name":"Jing M. Chen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00758585261378586,"gpt":0.2008715765402199,"spread":0.1932857239264341,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001523434,0.000792652,0.0001684904,0.0006557269,0.0001259543,0.0003609674,0.000201719,0.0002937465,0.0007681363],"category_scores_gemma":[0.0003477204,0.0001683782,0.0002613405,0.0007983798,0.0001492886,0.0005360331,0.0001922106,0.0001838336,0.0001586578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417683,"about_ca_system_score_gemma":0.0004199709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02541597,"about_ca_topic_score_gemma":0.02476878,"domain_scores_codex":[0.9999523,0.000004891861,0.000003642853,0.00001675383,0.00001027888,0.00001213312],"domain_scores_gemma":[0.999934,0.000009476608,0.00001607098,0.000008899173,0.00002416136,0.00000736613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005100085,0.0001856474,0.587292,0.0003425103,0.0005210989,0.0008111722,0.0001748229,0.2010396,0.1280487,0.001279787,0.006542465,0.07325206],"study_design_scores_gemma":[0.00009463265,0.0000460619,0.5019561,0.00004415852,0.0001921361,0.0001260121,0.0001428124,0.4755873,0.01755345,0.0006846967,0.00350246,0.00007021337],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909733,0.0002552997,0.002897459,0.00007342113,0.00002237561,0.00001450734,0.003547434,0.0003309092,0.001885279],"genre_scores_gemma":[0.9911969,0.000199844,0.002902272,0.00004426223,0.00001555114,0.00001084471,0.005250758,0.00003026853,0.0003492315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02541597,"threshold_uncertainty_score":0.05053604,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406759188","doi":"10.34133/remotesensing.0446","title":"Global Inequality of PM <sub>2.5</sub> Exposure and Ecological Possession over 2001–2020","year":2025,"lang":"en","type":"article","venue":"Journal of Remote Sensing","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Possession (linguistics); Inequality; Geography; Environmental science; Ecology; Mathematics; Biology","authors":[{"name":"J Chen","is_ca":false},{"name":"Zhenfeng Shao","is_ca":false},{"name":"Xueke Zheng","is_ca":false},{"name":"Bowen Cai","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01920934111184641,"gpt":0.2371227398459786,"spread":0.2179133987341322,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003847684,0.0002162767,0.0001697858,0.0007978369,0.0002419713,0.0008462032,0.0002760366,0.0004161724,0.001545269],"category_scores_gemma":[0.0009113446,0.0000958192,0.000381289,0.001811734,0.0003137211,0.0006441176,0.0008844036,0.0004934784,0.0002768066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006858452,"about_ca_system_score_gemma":0.0003847486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03742469,"about_ca_topic_score_gemma":0.0361141,"domain_scores_codex":[0.9998056,0.00003248996,0.00001883501,0.00005443453,0.00002313066,0.00006550697],"domain_scores_gemma":[0.9993455,0.00004912277,0.0003422413,0.00004513338,0.0001201644,0.00009772853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009474514,0.00002415159,0.9876434,0.00004839496,0.0000891403,0.0001585787,0.0006333353,0.0008958624,0.0003847922,0.0006441508,0.001458558,0.007924974],"study_design_scores_gemma":[8.689063e-7,0.0000111676,0.9984671,0.000008957164,0.00001047258,0.00004504849,0.0003248268,0.0002562106,0.00002416246,0.00005169274,0.0007968816,0.000002511939],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903358,0.0008051337,0.0001751298,0.0008746693,0.00003010168,0.000007039049,0.0046265,0.00001680352,0.003128733],"genre_scores_gemma":[0.9974311,0.0002287017,0.00005545528,0.0000769149,0.00001428797,0.000005665697,0.001843972,0.000002293738,0.0003415971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03742469,"threshold_uncertainty_score":0.07441372,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}