{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":232,"total_is_capped":false,"direct_labels_cover":1,"predictions_cover":232,"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":"90edaad7179a","filters":{"venue":"International Journal of Remote Sensing"}},"results":[{"id":"W2077570405","doi":"10.1080/01431160412331291297","title":"GLC2000: a new approach to global land cover mapping from Earth observation data","year":2005,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":1867,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Land cover; Vegetation (pathology); General partnership; Geography; Remote sensing; Geomatics; Earth observation; Database; Product (mathematics); Environmental resource management; Cover (algebra); Cartography; Land use; Computer science; Satellite; Political science; Environmental science; Engineering","authors":[{"name":"Étienne Bartholomé","is_ca":false},{"name":"Alan Belward","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04154139217003906,"gpt":0.2669772099775927,"spread":0.2254358178075537,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006004677,0.002024754,0.001526286,0.01770366,0.0008412219,0.00504965,0.003273556,0.001808889,0.01241549],"category_scores_gemma":[0.0161034,0.001368519,0.001833634,0.02094534,0.0004647271,0.002820489,0.003448514,0.00215634,0.008124659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001791151,"about_ca_system_score_gemma":0.002791155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0426783,"about_ca_topic_score_gemma":0.01740923,"domain_scores_codex":[0.9968459,0.0006938783,0.0003900461,0.0006637221,0.001240895,0.0001656242],"domain_scores_gemma":[0.99266,0.002068906,0.0006839763,0.00220579,0.001863301,0.0005180945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002933898,0.0002590273,0.01132091,0.001046751,0.0005589797,0.0004719636,0.000777847,0.03109059,0.004307471,0.01533275,0.4550312,0.4795091],"study_design_scores_gemma":[0.0003480531,0.00007619397,0.03135045,0.0006687001,0.0002661631,0.0004281948,0.0005845698,0.119936,0.004431802,0.02525998,0.8163251,0.0003248448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01565844,0.001272529,0.4500939,0.001230783,0.0005783797,0.001260092,0.4667536,0.04996958,0.01318273],"genre_scores_gemma":[0.02737821,0.0007132845,0.5501179,0.00036736,0.0001875263,0.001716998,0.4082296,0.007869027,0.003420179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0426783,"threshold_uncertainty_score":0.08485979,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2001510610","doi":"10.1080/01431161.2012.748992","title":"Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data","year":2012,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":1716,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Centre de Géomatique du Québec","funders":"","keywords":"Thematic Mapper; Land cover; Remote sensing; Moderate-resolution imaging spectroradiometer; Orthophoto; Cartography; Satellite imagery; Environmental science; Satellite; Geography; Land use","authors":[{"name":"Peng Gong","is_ca":false},{"name":"Jie Wang","is_ca":false},{"name":"Le Yu","is_ca":false},{"name":"Yongchao Zhao","is_ca":false},{"name":"Yuanyuan Zhao","is_ca":false},{"name":"Lü Liang","is_ca":false},{"name":"Zhenguo Niu","is_ca":false},{"name":"Xiaomeng Huang","is_ca":false},{"name":"Haohuan Fu","is_ca":false},{"name":"Shuang Liu","is_ca":false},{"name":"Congcong Li","is_ca":false},{"name":"Xueyan Li","is_ca":false},{"name":"Wei Fu","is_ca":false},{"name":"Caixia Liu","is_ca":false},{"name":"Yue‐Ping Xu","is_ca":false},{"name":"Xiaoyi Wang","is_ca":false},{"name":"Qu Cheng","is_ca":false},{"name":"Luanyun Hu","is_ca":false},{"name":"Wenbo Yao","is_ca":false},{"name":"Han Zhang","is_ca":false},{"name":"Peng Zhu","is_ca":false},{"name":"Ziying Zhao","is_ca":false},{"name":"Haiying Zhang","is_ca":false},{"name":"Yaomin Zheng","is_ca":false},{"name":"Luyan Ji","is_ca":false},{"name":"Ya‐Wen Zhang","is_ca":false},{"name":"Han Chen","is_ca":false},{"name":"Yan An","is_ca":false},{"name":"Jianhong Guo","is_ca":false},{"name":"Yu Liang","is_ca":false},{"name":"Lei Wang","is_ca":false},{"name":"Xiaojun Liu","is_ca":false},{"name":"Tingting Shi","is_ca":false},{"name":"Menghua Zhu","is_ca":false},{"name":"Yanlei Chen","is_ca":false},{"name":"Guangwen Yang","is_ca":false},{"name":"Ping Tang","is_ca":false},{"name":"Bing Xu","is_ca":false},{"name":"Chandra Giri","is_ca":false},{"name":"Nicholas Clinton","is_ca":false},{"name":"Zhiliang Zhu","is_ca":false},{"name":"Jin Chen","is_ca":true},{"name":"Jun Chen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03088526435108061,"gpt":0.2553800190547297,"spread":0.2244947547036491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001578635,0.0005150327,0.0004240612,0.001337573,0.0003185667,0.0005467888,0.000322881,0.0003188183,0.0009851294],"category_scores_gemma":[0.001507632,0.0001935318,0.0004767869,0.001903558,0.0001726134,0.0007145818,0.0005357991,0.0003131796,0.000404582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003438044,"about_ca_system_score_gemma":0.0002265063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01820949,"about_ca_topic_score_gemma":0.02880473,"domain_scores_codex":[0.9994888,0.000113365,0.00003987827,0.0001355174,0.0001586013,0.00006378318],"domain_scores_gemma":[0.9991016,0.0001331421,0.0001064181,0.0002509552,0.0003142462,0.00009366214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005125337,0.0007772552,0.6498041,0.0002731113,0.0002242404,0.0003894034,0.001069086,0.02716121,0.06827746,0.0004900903,0.005451524,0.2455701],"study_design_scores_gemma":[0.00003803368,0.0002481551,0.9706575,0.00001893998,0.00008455565,0.0001213109,0.000243574,0.01168176,0.01171389,0.0001379102,0.005016928,0.00003746416],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651775,0.0003599327,0.02073592,0.0001058718,0.00001808202,0.0003029713,0.00865917,0.0005900447,0.004050508],"genre_scores_gemma":[0.8869991,0.0002605225,0.09915131,0.00006629537,0.00002844028,0.0001833699,0.0116502,0.0001531856,0.001507555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01820949,"threshold_uncertainty_score":0.03620702,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2133160971","doi":"10.1080/01431160701736489","title":"Review of methods of small‐footprint airborne laser scanning for extracting forest inventory data in boreal forests","year":2008,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":632,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Canadian Forest Service; Canadian Sport Centre Pacific","funders":"","keywords":"Remote sensing; Laser scanning; Taiga; Forest inventory; Lidar; Environmental science; Tree canopy; Photogrammetry; Terrain; Canopy; Footprint; Tree (set theory); Geography; Forestry; Agroforestry; Forest management; Laser; Cartography; Mathematics","authors":[{"name":"Juha Hyyppä","is_ca":false},{"name":"Hannu Hyyppä","is_ca":false},{"name":"Donald G. Leckie","is_ca":true},{"name":"François A. Gougeon","is_ca":true},{"name":"Xiaowei Yu","is_ca":false},{"name":"Matti Maltamo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0809476343659227,"gpt":0.3733521418707554,"spread":0.2924045075048327,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002091169,0.0006306421,0.0007446663,0.004107506,0.0003853751,0.001178597,0.00111721,0.0005388391,0.002111873],"category_scores_gemma":[0.002655354,0.0005643328,0.0006407065,0.003790154,0.0004495157,0.001593174,0.0003062215,0.0003667965,0.001496063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004204443,"about_ca_system_score_gemma":0.0009678723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003437431,"about_ca_topic_score_gemma":0.004978907,"domain_scores_codex":[0.998925,0.0002019874,0.0001727567,0.0001727728,0.0005016678,0.00002575978],"domain_scores_gemma":[0.9970433,0.001679082,0.000158691,0.0001350969,0.0009503637,0.00003339737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003542181,0.00002769825,0.00118027,0.005859919,0.0000939493,0.0001232395,0.0001305359,0.001587487,0.007215657,0.001974392,0.005985406,0.9757861],"study_design_scores_gemma":[0.00002388267,0.0002449315,0.02559279,0.004037826,0.0003258456,0.002926776,0.0004801454,0.01139123,0.02368022,0.006474195,0.9246481,0.0001741438],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.008465161,0.5974925,0.3752571,0.0008002681,0.0009803753,0.0003948863,0.00100672,0.0007108784,0.01489217],"genre_scores_gemma":[0.0283086,0.4874577,0.4712851,0.0004450472,0.0007324517,0.0003777437,0.00143417,0.0001823725,0.009776948],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004107506,"threshold_uncertainty_score":0.01105928,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2794891691","doi":"10.1080/01431161.2018.1452075","title":"Land cover 2.0","year":2018,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":401,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Natural Resources Canada; University of British Columbia; Canadian Forest Service","funders":"Canadian Space Agency; National Aeronautics and Space Administration","keywords":"Land cover; Remote sensing; Advanced very-high-resolution radiometer; Earth observation; Context (archaeology); Thematic Mapper; Land information system; Computer science; Cover (algebra); Earth system science; Thematic map; Satellite; Data science; Land use; Satellite imagery; Geography; Land management; Cartography; Geology; Engineering","authors":[{"name":"Michael A. Wulder","is_ca":true},{"name":"Nicholas C. Coops","is_ca":true},{"name":"David P. Roy","is_ca":false},{"name":"Joanne C. White","is_ca":true},{"name":"Txomin Hermosilla","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008421781294441356,"gpt":0.2454367834271219,"spread":0.2370150021326805,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004179327,0.0007909882,0.0004576678,0.003652457,0.0005754272,0.002596087,0.00062724,0.0004415778,0.07816777],"category_scores_gemma":[0.001269885,0.0001317757,0.0004772425,0.006647039,0.0002944525,0.001613132,0.001387681,0.0005724521,0.06388966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007122817,"about_ca_system_score_gemma":0.001125989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01478695,"about_ca_topic_score_gemma":0.009011904,"domain_scores_codex":[0.9994212,0.00006570447,0.00004393146,0.0001297306,0.0002310408,0.0001083294],"domain_scores_gemma":[0.9995377,0.00003918368,0.00006787439,0.00005274828,0.0002344083,0.00006805081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007631924,0.00004717136,0.01215902,0.001265325,0.0000572352,0.0001973868,0.0003630895,0.0007734781,0.001339209,0.02950753,0.7481599,0.2060543],"study_design_scores_gemma":[0.000005001133,0.000009759355,0.009301184,0.0001515324,0.000009118381,0.0001431083,0.0001441034,0.0002284697,0.0001398367,0.002587114,0.9872651,0.0000157492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01075167,0.008189531,0.006849504,0.002483945,0.001161921,0.0004962606,0.4895083,0.003285071,0.4772737],"genre_scores_gemma":[0.1066359,0.01176003,0.01620353,0.003089397,0.001127506,0.0008623968,0.686362,0.001422292,0.1725369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07816777,"threshold_uncertainty_score":0.2614972,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012116092","doi":"10.1080/01431160500075857","title":"Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer","year":2005,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":345,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; Canadian Space Agency; European Space Agency; Australian Government","keywords":"Radiance; Imaging spectrometer; Remote sensing; Environmental science; Satellite; Spectrometer; Ocean color; Oceanography; Geology; Physics; Optics; Astronomy","authors":[{"name":"Jim Gower","is_ca":true},{"name":"Stephanie King","is_ca":true},{"name":"Gary A. Borstad","is_ca":false},{"name":"Leslie Brown","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00955445938651113,"gpt":0.2156044123818768,"spread":0.2060499529953657,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001684755,0.0002199054,0.0001274038,0.0004711894,0.0001848744,0.000201953,0.0001099466,0.0001684446,0.0007729218],"category_scores_gemma":[0.0001532343,0.0001169276,0.000100387,0.0002486671,0.00009626833,0.0002311939,0.0001557355,0.0001290653,0.0002428202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001971454,"about_ca_system_score_gemma":0.00009059076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002489729,"about_ca_topic_score_gemma":0.008906887,"domain_scores_codex":[0.9999291,0.000009863505,0.000002689085,0.000018375,0.00003137615,0.000008649318],"domain_scores_gemma":[0.9999149,0.00001716455,0.00001920867,0.000005707019,0.00002812337,0.00001485512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004991099,0.0000741671,0.1566141,0.00008644772,0.00007206093,0.0001720005,0.0002090281,0.002028255,0.7878381,0.0004157553,0.002253478,0.04973756],"study_design_scores_gemma":[0.00004426399,0.0002068473,0.65936,0.00001945359,0.00005649708,0.0005630606,0.0003032736,0.03396174,0.3006264,0.0003433491,0.004467385,0.00004781567],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910226,0.0001492447,0.003525173,0.00007673263,0.00001266728,0.000007856499,0.0004180585,0.0002384441,0.004549239],"genre_scores_gemma":[0.9871283,0.0001460299,0.01085141,0.00004225272,0.000009326971,0.000006454322,0.0003771333,0.00001691349,0.0014222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002489729,"threshold_uncertainty_score":0.004950523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2144362041","doi":"10.1080/01431160310001618464","title":"Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case","year":2004,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":277,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Land cover; Remote sensing; Image resolution; Contextual image classification; Geography; Window (computing); Cartography; Classifier (UML); Computer science; Texture (cosmology); Artificial intelligence; Land use; Image (mathematics)","authors":[{"name":"Dongmei Chen","is_ca":false},{"name":"D. A. Stow","is_ca":false},{"name":"Peng Gong","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01328333869139886,"gpt":0.2432140190719095,"spread":0.2299306803805106,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006294383,0.0004257782,0.0004091762,0.0007565324,0.0005064122,0.001453415,0.0004681961,0.0005674108,0.001004309],"category_scores_gemma":[0.03329185,0.0002343878,0.0003921474,0.001185151,0.000708472,0.001016077,0.0006349022,0.0004615939,0.0002441313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006625023,"about_ca_system_score_gemma":0.0002957413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009632802,"about_ca_topic_score_gemma":0.008999193,"domain_scores_codex":[0.9960006,0.002249479,0.0001868548,0.0004436694,0.0008424493,0.0002769667],"domain_scores_gemma":[0.9481281,0.04452388,0.001797739,0.001462564,0.003767564,0.0003200097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00433103,0.0008689032,0.6160986,0.0003048017,0.0005059739,0.001214506,0.001446875,0.1823252,0.02397772,0.001039322,0.001303056,0.166584],"study_design_scores_gemma":[0.0001488505,0.001747565,0.5100066,0.00008616449,0.0004362425,0.0006571864,0.002898423,0.4500051,0.03048385,0.00190777,0.001514717,0.0001076789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923529,0.0001794523,0.006003526,0.0001041225,0.000008586421,0.00003454452,0.00009342948,0.00003823752,0.001185201],"genre_scores_gemma":[0.9953181,0.00004330224,0.004379957,0.00001655857,0.00000706676,0.000009867405,0.00006469483,0.00001364866,0.0001468068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009632802,"threshold_uncertainty_score":0.0332883,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2034671455","doi":"10.1080/01431160050030592","title":"Destriping multisensor imagery with moment matching","year":2000,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":255,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Golder Associates (Canada); University of Toronto","funders":"Delta Waterfowl; University of Toronto","keywords":"Histogram; Outlier; Histogram matching; Moment (physics); Artificial intelligence; Matching (statistics); Computer science; Offset (computer science); Computer vision; Histogram equalization; Pattern recognition (psychology); Mathematics; Statistics; Image (mathematics)","authors":[{"name":"F. L. Gadallah","is_ca":true},{"name":"F. Csillag","is_ca":true},{"name":"Eric Smith","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01632281076912038,"gpt":0.2835757035005704,"spread":0.26725289273145,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009987621,0.0006712222,0.001007842,0.001573651,0.0004086997,0.0009381871,0.001096881,0.00102859,0.001908384],"category_scores_gemma":[0.003121158,0.0005837476,0.00118554,0.001587078,0.000567094,0.001727922,0.001529614,0.0009988681,0.001446217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004666657,"about_ca_system_score_gemma":0.0005120765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001043546,"about_ca_topic_score_gemma":0.00132905,"domain_scores_codex":[0.9992564,0.0001041488,0.00004579661,0.0001815431,0.0003474159,0.00006460617],"domain_scores_gemma":[0.9991035,0.0002390839,0.0001448168,0.00029541,0.0001801864,0.00003698985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004027844,0.000108858,0.001066616,0.0001814796,0.0001381233,0.0001376735,0.0001973474,0.0488546,0.130783,0.01000068,0.001873972,0.8062549],"study_design_scores_gemma":[0.00003520397,0.0001842909,0.003553279,0.00002351125,0.00007023408,0.0005786975,0.00008199457,0.8389646,0.1335715,0.01444072,0.008423192,0.00007274646],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009172218,0.00008970367,0.9892243,0.00004227993,0.00003025653,0.00003503204,0.00002912413,0.0008723913,0.0005047889],"genre_scores_gemma":[0.09701011,0.0001532901,0.9009847,0.0000473869,0.00004329395,0.00006116318,0.0001844446,0.0001999913,0.001315662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001908384,"threshold_uncertainty_score":0.006384194,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2152334070","doi":"10.1080/01431160903571791","title":"Comparison of pixel- and object-based classification in land cover change mapping","year":2011,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":230,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Carleton University","funders":"Vlaamse regering","keywords":"Thematic Mapper; Thematic map; Land cover; Change detection; Cartography; Remote sensing; Pixel; Object (grammar); Land use; Geography; Computer science; Data mining; Artificial intelligence; Satellite imagery; Ecology","authors":[{"name":"Laura Dingle Robertson","is_ca":true},{"name":"Douglas J. King","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0803817342266771,"gpt":0.2913954218955067,"spread":0.2110136876688296,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007461547,0.0004287752,0.0004968113,0.00342159,0.0003279687,0.001954375,0.0005012653,0.000659165,0.000760505],"category_scores_gemma":[0.01523929,0.0002208141,0.0003336959,0.003771165,0.000458567,0.001303699,0.0005264831,0.0002440499,0.000344308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061679,"about_ca_system_score_gemma":0.0005630522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02447162,"about_ca_topic_score_gemma":0.03975077,"domain_scores_codex":[0.9961403,0.001846166,0.0002035427,0.0003364404,0.001298504,0.0001750383],"domain_scores_gemma":[0.9918315,0.004857571,0.0003524324,0.0006140923,0.002202961,0.0001414317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002930098,0.0002864766,0.3726134,0.0007026787,0.0008957086,0.000182477,0.002562571,0.02515058,0.01568409,0.002531098,0.002150791,0.5743099],"study_design_scores_gemma":[0.0001229453,0.0006484764,0.8375431,0.00009859448,0.0004851121,0.0002696697,0.001847275,0.1421444,0.009013877,0.001992323,0.005729766,0.0001043397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9440709,0.001282811,0.04446889,0.0001659002,0.00009908846,0.0002197447,0.001152887,0.0003481307,0.008191749],"genre_scores_gemma":[0.9608728,0.0003587974,0.03690724,0.00004526374,0.00002240927,0.00008041495,0.000823122,0.00008180477,0.0008081599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02447162,"threshold_uncertainty_score":0.04865831,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115076670","doi":"10.1080/014311601750038857","title":"Evaluation of C-band SAR data for wetlands mapping","year":2001,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":208,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Glaucoma Research Society of Canada","keywords":"Wetland; Remote sensing; Polarimetry; Bog; Synthetic aperture radar; Environmental science; Vegetation classification; Polarization (electrochemistry); Vegetation (pathology); Peat; Geology; Geography; Scattering; Physics; Ecology","authors":[{"name":"Nicolas Baghdadi","is_ca":true},{"name":"Monique Bernier","is_ca":true},{"name":"R. Gauthier","is_ca":false},{"name":"Ian Neeson","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05704297600137583,"gpt":0.321736391645533,"spread":0.2646934156441572,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003238919,0.000524994,0.0002982219,0.001562161,0.0003129904,0.0006924668,0.0004282036,0.0003980808,0.0009653742],"category_scores_gemma":[0.005870468,0.00009930346,0.0002470792,0.001084047,0.0001842548,0.0006617536,0.0003220516,0.0002699237,0.0004654108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005281317,"about_ca_system_score_gemma":0.0003870051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01137445,"about_ca_topic_score_gemma":0.01416994,"domain_scores_codex":[0.9983088,0.0006050404,0.00010186,0.0001539225,0.0007291355,0.000101247],"domain_scores_gemma":[0.9946509,0.001850942,0.0001999482,0.0003820118,0.002721566,0.0001947396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00390619,0.0008522072,0.127676,0.0005531231,0.0003488372,0.000443212,0.0004284637,0.1417242,0.1371967,0.000960656,0.00536385,0.5805467],"study_design_scores_gemma":[0.0003404949,0.002256697,0.2224748,0.0001035409,0.0002472496,0.0004525725,0.0009141299,0.6348965,0.1230358,0.0005605407,0.01458086,0.000136843],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9520242,0.0003972885,0.03522239,0.0002176918,0.0000708224,0.0004486362,0.002329626,0.0009078669,0.00838152],"genre_scores_gemma":[0.9463864,0.0001916274,0.04805101,0.00006223503,0.00002443261,0.00008405966,0.003797048,0.00006810853,0.001335143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01137445,"threshold_uncertainty_score":0.02261645,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2215770970","doi":"10.1080/2150704x.2015.1126375","title":"Forest recovery trends derived from Landsat time series for North American boreal forests","year":2015,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":186,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey","keywords":"Normalized Difference Vegetation Index; Taiga; Pixel; Disturbance (geology); Vegetation (pathology); Environmental science; Boreal; Physical geography; Remote sensing; Spectral bands; Forestry; Geography; Leaf area index; Ecology; Geology; Biology; Physics","authors":[{"name":"Paul D. Pickell","is_ca":true},{"name":"Txomin Hermosilla","is_ca":true},{"name":"Ryan J. Frazier","is_ca":true},{"name":"Nicholas C. Coops","is_ca":true},{"name":"Michael A. Wulder","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01119393416384829,"gpt":0.2381872794125363,"spread":0.226993345248688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006282829,0.0001608009,0.0001087931,0.001180916,0.0001801683,0.0002506213,0.0001286671,0.0001176987,0.000366004],"category_scores_gemma":[0.001453055,0.00007212416,0.0001806424,0.0009258813,0.00009247174,0.0003137738,0.0001172258,0.000151746,0.0001048323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000334748,"about_ca_system_score_gemma":0.0001599116,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02680744,"about_ca_topic_score_gemma":0.06681496,"domain_scores_codex":[0.9998455,0.00002240607,0.00002367207,0.00003664898,0.0000518432,0.0000198951],"domain_scores_gemma":[0.9989156,0.000186256,0.0004809976,0.00007014721,0.0002892382,0.0000577968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008004045,0.0000425156,0.9887109,0.00001959096,0.00003036492,0.00003559501,0.0001062814,0.001283736,0.001411348,0.00002746276,0.0002644784,0.007987608],"study_design_scores_gemma":[9.008007e-7,0.00002411386,0.9977987,0.000001872813,0.000006740117,0.00003124914,0.00004866277,0.00178184,0.0001351204,0.000005957931,0.0001628086,0.000001956886],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979132,0.00005117843,0.000246881,0.000009258555,0.000001734651,0.000006433453,0.001455813,0.00002076938,0.0002946658],"genre_scores_gemma":[0.9950766,0.00004002812,0.0007453507,0.000004658199,0.000003476299,0.00001257587,0.003985762,0.00000396405,0.0001276437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9731926,"threshold_uncertainty_score":0.05330276,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2167753478","doi":"10.1080/01431161.2013.788261","title":"Integration of orthoimagery and lidar data for object-based urban thematic mapping using random forests","year":2013,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":176,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Computer science; Multispectral image; Artificial intelligence; Random forest; Lidar; Orthophoto; Thematic Mapper; Segmentation; Aerial image; Pattern recognition (psychology); Thematic map; Image segmentation; Feature (linguistics); Feature selection; Classifier (UML); Pixel; Remote sensing; Satellite imagery; Image (mathematics); Geography; Cartography","authors":[{"name":"Haiyan Guan","is_ca":true},{"name":"Jonathan Li","is_ca":true},{"name":"Michael A. Chapman","is_ca":true},{"name":"Fei Deng","is_ca":false},{"name":"Zheng Ji","is_ca":false},{"name":"Yang Xu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03133330515750703,"gpt":0.272343004543332,"spread":0.2410096993858249,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001268031,0.0005935458,0.0005880228,0.001661578,0.0003848128,0.0004641589,0.0005341865,0.0003314631,0.0005975976],"category_scores_gemma":[0.001651039,0.0003231406,0.0008759175,0.001289953,0.0001920183,0.000828342,0.0003760371,0.0004342967,0.0004681935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002473425,"about_ca_system_score_gemma":0.0004974894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005680111,"about_ca_topic_score_gemma":0.01035489,"domain_scores_codex":[0.9995047,0.0001530891,0.00002630145,0.00009943931,0.0001676622,0.00004884402],"domain_scores_gemma":[0.9994316,0.0002485093,0.00005982214,0.00008166711,0.0001541904,0.00002431436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000354192,0.0003423573,0.01452493,0.00019783,0.0003118665,0.0001925886,0.0001847496,0.1779639,0.07455107,0.001158454,0.001215853,0.7290022],"study_design_scores_gemma":[0.00001917514,0.0001110548,0.01366235,0.00002017934,0.0001293418,0.0001565293,0.00008295697,0.9541564,0.02821713,0.001631385,0.001766405,0.00004716933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1264436,0.0002443564,0.8701771,0.00004654365,0.00001942839,0.00008974972,0.0001647952,0.001951126,0.0008630722],"genre_scores_gemma":[0.4616985,0.0001493166,0.5368018,0.00002331626,0.00001451015,0.0000966408,0.000659588,0.0001354229,0.0004209497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005680111,"threshold_uncertainty_score":0.01129413,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2109931483","doi":"10.1080/01431160701408477","title":"ASTER DEMs for geomatic and geoscientific applications: a review","year":2008,"lang":"en","type":"review","venue":"International Journal of Remote Sensing","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":172,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Remote sensing; Advanced Spaceborne Thermal Emission and Reflection Radiometer; Digital elevation model; Geomatics; Stereoscopy; Geospatial analysis; Orthophoto; Digitization; Photogrammetry; Geolocation; Satellite; Georeference; Terrain; Computer science; Earth observation; Satellite imagery; Elevation (ballistics); Geographic information system; Geology; Geography; Cartography; Artificial intelligence; Computer vision","authors":[{"name":"Thierry Toutin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0351450420129456,"gpt":0.33071896089812,"spread":0.2955739188851744,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001856166,0.001226667,0.001099009,0.005142448,0.0003008145,0.001484894,0.001906402,0.001033445,0.005470483],"category_scores_gemma":[0.003422545,0.0005255255,0.0007573261,0.008668758,0.0005515348,0.003292596,0.0008233775,0.001221755,0.00404409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005372083,"about_ca_system_score_gemma":0.001128554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002468989,"about_ca_topic_score_gemma":0.00241973,"domain_scores_codex":[0.9993999,0.0001044692,0.00009010657,0.00008644779,0.0002938635,0.00002524597],"domain_scores_gemma":[0.9975465,0.001184026,0.0002203146,0.0001165614,0.000873587,0.00005893448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002874506,0.00003753885,0.0004022543,0.007887008,0.00005701252,0.00007882485,0.00006412828,0.002100403,0.0009215524,0.004592177,0.03895447,0.944876],"study_design_scores_gemma":[0.00000895579,0.00003580598,0.001180759,0.002934616,0.00008108893,0.0004182583,0.00009302478,0.001590315,0.000946354,0.002512793,0.9901503,0.00004784648],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009635345,0.9720998,0.0162103,0.0009721734,0.0008949899,0.0001008037,0.001093127,0.000437842,0.007227391],"genre_scores_gemma":[0.003726724,0.9748973,0.01782035,0.0002510755,0.0004154322,0.00006396757,0.001369258,0.0000893683,0.001366671],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005470483,"threshold_uncertainty_score":0.01830059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994809198","doi":"10.1080/01431160701736505","title":"Mapping the height and above‐ground biomass of a mixed forest using lidar and stereo Ikonos images","year":2008,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":143,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Lidar; Remote sensing; Digital elevation model; Elevation (ballistics); Multispectral image; Environmental science; Terrain; Digital surface; Photogrammetry; Canopy; Percentile; Ranging; Geography; Geodesy; Cartography; Mathematics; Statistics","authors":[{"name":"Benoît St-Onge","is_ca":true},{"name":"Yongxiang Hu","is_ca":true},{"name":"Cédric Vega","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02632519518935333,"gpt":0.2516140571718428,"spread":0.2252888619824895,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008714568,0.0002057342,0.0001575364,0.0009553194,0.0001815086,0.0002467614,0.0002127633,0.0001940231,0.00091935],"category_scores_gemma":[0.0001321882,0.0001933927,0.000193911,0.0004811431,0.00007671914,0.0002739979,0.0001543977,0.0001204682,0.0002449013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710684,"about_ca_system_score_gemma":0.0003313785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01257775,"about_ca_topic_score_gemma":0.02290522,"domain_scores_codex":[0.9999623,0.000002271671,0.000001429635,0.00001164351,0.00001305597,0.000009258035],"domain_scores_gemma":[0.9999423,0.0000100132,0.000008777527,0.000005535415,0.00001566243,0.00001772114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008317918,0.0004061217,0.2458192,0.0001324931,0.0002094249,0.0003801362,0.0003198737,0.03086966,0.4980064,0.0005826225,0.002144341,0.2202979],"study_design_scores_gemma":[0.0000686159,0.0001191198,0.7711157,0.00001864346,0.0001278294,0.0002796536,0.0003276455,0.1972784,0.02894079,0.0004195188,0.001264936,0.00003921902],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930919,0.00005042626,0.004777697,0.00002004524,0.00000609884,0.00001094716,0.0007736821,0.0001147067,0.001154436],"genre_scores_gemma":[0.9837285,0.000046824,0.01472559,0.0000100353,0.000006226735,0.00001094384,0.0009280641,0.00001100948,0.0005329027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01257775,"threshold_uncertainty_score":0.02500904,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1965362766","doi":"10.1080/01431161.2012.700133","title":"Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach","year":2012,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Canadian Space Agency","keywords":"Support vector machine; Land cover; Remote sensing; Synthetic aperture radar; Polarimetry; Computer science; Cohen's kappa; Contextual image classification; Pattern recognition (psychology); Environmental science; Artificial intelligence; Geography; Land use; Machine learning; Image (mathematics)","authors":[{"name":"Xin Niu","is_ca":false},{"name":"Yifang Ban","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05743423422570928,"gpt":0.3040385935813299,"spread":0.2466043593556206,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00203864,0.0005074,0.000620477,0.001591397,0.0002126717,0.001065597,0.0006127397,0.0005622997,0.0006802087],"category_scores_gemma":[0.002935078,0.0002105399,0.0007790342,0.001031825,0.0002332088,0.0009504777,0.0002621026,0.0004510296,0.0004203448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00033519,"about_ca_system_score_gemma":0.0004053317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002087938,"about_ca_topic_score_gemma":0.002728499,"domain_scores_codex":[0.9991363,0.0002146272,0.0001063761,0.0001552561,0.0003161864,0.00007123255],"domain_scores_gemma":[0.9983665,0.0005978595,0.0001602243,0.000195873,0.0006306097,0.00004889521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003672385,0.0005782222,0.03607165,0.0002309957,0.0002198108,0.0004096463,0.0001961048,0.2254042,0.05628839,0.001180213,0.001150275,0.6779032],"study_design_scores_gemma":[0.00001253964,0.0001837335,0.01297269,0.00002821341,0.00005517494,0.000115519,0.0001083901,0.9684614,0.016365,0.0007571842,0.0009087606,0.00003140812],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5450391,0.0006397069,0.4492227,0.0003050567,0.00007851959,0.0001994722,0.000568864,0.001124961,0.00282165],"genre_scores_gemma":[0.7485696,0.0002318605,0.2492808,0.00006725214,0.00003579721,0.00009525369,0.0006798175,0.0000321363,0.001007458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002087938,"threshold_uncertainty_score":0.01078153,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2463336507","doi":"10.1080/01431161.2016.1194545","title":"Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity","year":2016,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":123,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Russian Science Foundation; European Commission","keywords":"Moderate-resolution imaging spectroradiometer; Remote sensing; Pairwise comparison; Environmental science; Data set; Computer science; Thematic map; Baseline (sea); Calibration; Image resolution; Satellite; Statistics; Cartography; Geography; Mathematics; Artificial intelligence","authors":[{"name":"François Waldner","is_ca":false},{"name":"Diego de Abelleyra","is_ca":false},{"name":"Santiago R. Verón","is_ca":false},{"name":"Miao Zhang","is_ca":false},{"name":"Bingfang Wu","is_ca":false},{"name":"Д.Е. Плотников","is_ca":false},{"name":"С.А. Барталев","is_ca":false},{"name":"Mykola Lavreniuk","is_ca":false},{"name":"Sergii Skakun","is_ca":false},{"name":"Nataliia Kussul","is_ca":false},{"name":"Guerric Le Maire","is_ca":false},{"name":"Stéphane Dupuy","is_ca":false},{"name":"Ian Jarvis","is_ca":true},{"name":"Pierre Defourny","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02811484508570678,"gpt":0.2970490568489803,"spread":0.2689342117632735,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002454669,0.000861322,0.0007849842,0.003138981,0.0004409411,0.001307151,0.001036738,0.0004931309,0.0006489742],"category_scores_gemma":[0.002815755,0.0002202243,0.0007164307,0.001641748,0.0002629448,0.001128687,0.0008825479,0.0006895196,0.0004797015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004765322,"about_ca_system_score_gemma":0.0009814786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001920231,"about_ca_topic_score_gemma":0.004045723,"domain_scores_codex":[0.9991283,0.000259532,0.00005477779,0.0003140478,0.0002040286,0.00003931546],"domain_scores_gemma":[0.9988075,0.0002476267,0.0002361778,0.0002113935,0.0004421295,0.00005509041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008992611,0.0003541017,0.0752326,0.0006438051,0.0004148319,0.00008519272,0.0004572418,0.04835075,0.04321863,0.003548483,0.002340843,0.8252636],"study_design_scores_gemma":[0.00006345403,0.0006512389,0.2882606,0.0007537599,0.0004815624,0.0005823083,0.001433633,0.600666,0.0552693,0.01386838,0.03775262,0.0002172274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08650383,0.001517954,0.9058729,0.0001835188,0.00004739081,0.0002713458,0.001052491,0.00129251,0.003258086],"genre_scores_gemma":[0.1592093,0.0005878861,0.8374761,0.00006444807,0.00002864687,0.0002963735,0.001463119,0.0001136888,0.0007604441],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003138981,"threshold_uncertainty_score":0.01298165,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1967005377","doi":"10.1080/01431161.2012.756596","title":"InSAR time-series analysis of land subsidence in Bangkok, Thailand","year":2013,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":120,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Space Agency; Chulalongkorn University; European Commission","keywords":"Levelling; Interferometric synthetic aperture radar; Subsidence; Series (stratigraphy); Geology; Flooding (psychology); Water level; Synthetic aperture radar; Physical geography; Geodesy; Remote sensing; Geography; Geomorphology; Cartography","authors":[{"name":"Anuphao Aobpaet","is_ca":false},{"name":"Miguel Caro Cuenca","is_ca":false},{"name":"Andrew Hooper","is_ca":false},{"name":"Itthi Trisirisatayawong","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005757996154143274,"gpt":0.2242752312695768,"spread":0.2185172351154336,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002050499,0.0003831405,0.0002437596,0.0007570916,0.0002663986,0.0006125724,0.0002361448,0.0001860403,0.0005844273],"category_scores_gemma":[0.0005203612,0.0001619601,0.0001915078,0.001742267,0.0002543862,0.0002778219,0.0002698844,0.0001906838,0.0002353134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00061206,"about_ca_system_score_gemma":0.000527112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0950259,"about_ca_topic_score_gemma":0.08468082,"domain_scores_codex":[0.9998746,0.00001713545,0.00001468258,0.00002848865,0.00003104694,0.00003409924],"domain_scores_gemma":[0.9996456,0.00005644609,0.00007637295,0.00003647209,0.0001198285,0.00006526976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008022208,0.0002218746,0.8107772,0.0002975358,0.0003837087,0.003251435,0.001022594,0.111461,0.02408001,0.000501621,0.003162419,0.04403837],"study_design_scores_gemma":[0.00001311652,0.00003393423,0.9451807,0.00001568995,0.00004405435,0.0001708243,0.0007215652,0.05161595,0.00140512,0.00004560006,0.0007290737,0.00002440036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977807,0.00006374386,0.0002351365,0.00002309942,0.000003419799,0.000004692074,0.001285831,0.00002951904,0.0005738398],"genre_scores_gemma":[0.9969534,0.00007913966,0.0002267745,0.00000559213,0.000002569667,0.000003976769,0.002456419,0.000005195833,0.0002669214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0950259,"threshold_uncertainty_score":0.1889456,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2080849056","doi":"10.1080/01431160512331326567","title":"Usefulness and limits of MODIS GPP for estimating wheat yield","year":2005,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":112,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"McMaster University; U.S. Department of Agriculture; National Aeronautics and Space Administration","keywords":"Yield (engineering); Moderate-resolution imaging spectroradiometer; Environmental science; Productivity; Climatology; Physical geography; Statistics; Mathematics; Geography; Satellite; Geology; Economics","authors":[{"name":"Matthew C. Reeves","is_ca":false},{"name":"Maosheng Zhao","is_ca":false},{"name":"S. W. Running","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02342179229089441,"gpt":0.266000275147829,"spread":0.2425784828569346,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009530166,0.0004606055,0.0004758459,0.0009541316,0.0005912424,0.002594479,0.0008215166,0.0009305186,0.0002456181],"category_scores_gemma":[0.05643128,0.000443841,0.0004981694,0.001227988,0.001068891,0.002443781,0.00143956,0.0009820309,0.0001991002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009252447,"about_ca_system_score_gemma":0.0006262473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008293234,"about_ca_topic_score_gemma":0.00614172,"domain_scores_codex":[0.9960189,0.001802392,0.0003800587,0.0006321943,0.001042375,0.000123973],"domain_scores_gemma":[0.978337,0.01494557,0.001415548,0.002747405,0.002343583,0.0002108203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006591793,0.00008991673,0.6015031,0.0004570509,0.0002817195,0.0007322517,0.002847524,0.1001354,0.0137044,0.0133667,0.003220157,0.2630027],"study_design_scores_gemma":[0.0001134548,0.0002947838,0.3887624,0.0004825396,0.0003011029,0.001807804,0.002173348,0.5469334,0.01689314,0.02785065,0.01414892,0.0002384773],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9041914,0.00334133,0.07940283,0.002366908,0.00005420465,0.00004078534,0.0005787942,0.0005399247,0.009483762],"genre_scores_gemma":[0.9722804,0.0005353328,0.02654962,0.00007652052,0.00004408382,0.00003207185,0.0002621274,0.00004308633,0.0001768252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009530166,"threshold_uncertainty_score":0.05040097,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2166808775","doi":"10.1080/01431160110070753","title":"Providing crop information using RADARSAT-1 and satellite optical imagery","year":2002,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":107,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Remote sensing; Environmental science; Backscatter (email); Satellite imagery; Crop; Satellite; Radar; Geography; Computer science; Forestry","authors":[{"name":"Heather McNairn","is_ca":false},{"name":"James Ellis","is_ca":false},{"name":"J.J. van der Sanden","is_ca":false},{"name":"T. Hirose","is_ca":false},{"name":"R.J. Brown","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01340035900164779,"gpt":0.2284540665426503,"spread":0.2150537075410025,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004814916,0.000329369,0.0002972205,0.001821608,0.0004555514,0.0005829542,0.0003309951,0.0002371568,0.001889289],"category_scores_gemma":[0.0009738977,0.0002218689,0.0001387733,0.002103116,0.0001596975,0.0004815969,0.0003651377,0.0002329881,0.000652333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597422,"about_ca_system_score_gemma":0.002550404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3346305,"about_ca_topic_score_gemma":0.6936687,"domain_scores_codex":[0.999803,0.00001553133,0.00001004883,0.00003017624,0.0001036124,0.00003774107],"domain_scores_gemma":[0.9995952,0.00004795057,0.00004581842,0.00003923186,0.0002386549,0.00003303055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003004794,0.0001569411,0.07851929,0.0006042721,0.0001031591,0.0004276424,0.0006839642,0.006285237,0.07796251,0.001308758,0.01413667,0.8195112],"study_design_scores_gemma":[0.000124777,0.0002362879,0.7639733,0.0002272933,0.0002458893,0.00101803,0.001621241,0.04286873,0.05827942,0.001968905,0.1292449,0.0001911528],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8472233,0.007236056,0.05882099,0.001185316,0.0001756926,0.0007134984,0.03510555,0.001881609,0.04765805],"genre_scores_gemma":[0.7596415,0.004915717,0.2044858,0.0003575511,0.00007142768,0.00008549157,0.01819335,0.0001082285,0.01214091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3346305,"threshold_uncertainty_score":0.6653655,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108094322","doi":"10.1080/01431161.2014.960614","title":"The Jeffries–Matusita distance for the case of complex Wishart distribution as a separability criterion for fully polarimetric SAR data","year":2014,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":106,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary; Environment and Climate Change Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; ArcticNet","keywords":"Wishart distribution; Polarimetry; Pattern recognition (psychology); Artificial intelligence; Synthetic aperture radar; Covariance matrix; Inverse-Wishart distribution; Covariance; Computer science; Selection (genetic algorithm); Mathematics; Algorithm; Statistics; Machine learning; Multivariate statistics; Physics","authors":[{"name":"Mohammed Dabboor","is_ca":true},{"name":"Stephen Howell","is_ca":true},{"name":"Mohamed Shokr","is_ca":true},{"name":"John Yackel","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02704762639357829,"gpt":0.3157515846951136,"spread":0.2887039583015353,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002339841,0.0005452234,0.0006182931,0.001648535,0.0005022678,0.001631547,0.0006550805,0.0009624248,0.001213784],"category_scores_gemma":[0.007893889,0.0001661351,0.0007507596,0.0009764052,0.001202656,0.00215249,0.001026888,0.001122198,0.0005431937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005854345,"about_ca_system_score_gemma":0.0007442548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001725435,"about_ca_topic_score_gemma":0.001065525,"domain_scores_codex":[0.9987594,0.0003788374,0.0001201724,0.0002170594,0.0004483955,0.00007622792],"domain_scores_gemma":[0.9970604,0.001641559,0.0003618705,0.000295278,0.0005465042,0.00009431409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002927436,0.0001429219,0.005798972,0.0002851343,0.0002240176,0.0007290896,0.0004455088,0.341073,0.03841237,0.3706919,0.004048132,0.2378561],"study_design_scores_gemma":[0.000005025462,0.00004070747,0.002359778,0.00001345619,0.00001549334,0.0002507715,0.00002413672,0.9291404,0.006023609,0.06010213,0.001976738,0.00004765185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01913425,0.0003196945,0.9787593,0.00014198,0.00002884814,0.00002003215,0.00005610494,0.00008007521,0.001459696],"genre_scores_gemma":[0.4048488,0.0009595743,0.5878347,0.0002351484,0.0002793271,0.0001653687,0.000840958,0.0002180967,0.004617918],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002339841,"threshold_uncertainty_score":0.0123744,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2056254247","doi":"10.1080/01431160210154056","title":"Monitoring secondary tropical forests using space-borne data: Implications for Central America","year":2003,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":106,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Synthetic aperture radar; Remote sensing; Carbon sequestration; Environmental science; Carbon sink; Amazon rainforest; Biomass (ecology); Radar; Stratification (seeds); Geography; Climate change; Ecology; Computer science","authors":[{"name":"K. L. Castro","is_ca":true},{"name":"Arturo Sánchez‐Azofeifa","is_ca":true},{"name":"Benoît Rivard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0368091106949423,"gpt":0.3179247856784023,"spread":0.28111567498346,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001124004,0.0003439554,0.0002522389,0.000778215,0.0003354787,0.001101218,0.0005433301,0.0003768078,0.0007859033],"category_scores_gemma":[0.00127656,0.00008652671,0.0001790032,0.001450052,0.0002488097,0.0007808384,0.0005568182,0.0002382578,0.00007218409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007211157,"about_ca_system_score_gemma":0.00110603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05648863,"about_ca_topic_score_gemma":0.1133823,"domain_scores_codex":[0.9998152,0.00005186571,0.00002166481,0.00002718812,0.00005498576,0.0000291227],"domain_scores_gemma":[0.9989455,0.0002584966,0.0001559599,0.00005263831,0.0004582414,0.0001291749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003516547,0.0001398316,0.6344227,0.0007972432,0.0001511394,0.0009121481,0.001179634,0.005641143,0.04030839,0.001523016,0.003106248,0.3114669],"study_design_scores_gemma":[0.00009125348,0.0005318316,0.9199641,0.0007200651,0.0004403353,0.001467435,0.006090369,0.01621916,0.01099531,0.003015811,0.04038922,0.00007521111],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9282355,0.02963473,0.01372061,0.006567796,0.0001022701,0.0004001337,0.00266252,0.0003057467,0.01837076],"genre_scores_gemma":[0.9727065,0.008827786,0.01487869,0.0004881064,0.00006652127,0.0001266521,0.0006446672,0.00001819831,0.002242976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05648863,"threshold_uncertainty_score":0.1123196,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2158848000","doi":"10.1080/01431160512331314029","title":"A practical approach for estimating the red edge position of plant leaf reflectance","year":2005,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":98,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary; University of Waterloo","funders":"","keywords":"Red edge; Herbaceous plant; Remote sensing; Reflectivity; Inversion (geology); Vegetation (pathology); Environmental science; Chlorophyll; Wavelength; Spectral line; Position (finance); Mathematics; Botany; Hyperspectral imaging; Geology; Optics; Biology; Physics","authors":[{"name":"Gladimir V. G. Baranoski","is_ca":true},{"name":"Jon Rokne","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0237190866835556,"gpt":0.2995959007938599,"spread":0.2758768141103043,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000814303,0.001004367,0.000734195,0.001359512,0.0004815033,0.0008474163,0.0009480259,0.001179463,0.002219652],"category_scores_gemma":[0.002287388,0.0005014036,0.0005050684,0.0009562406,0.0003871482,0.0008909561,0.0007617333,0.001073458,0.001751908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002467216,"about_ca_system_score_gemma":0.0006178963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001810588,"about_ca_topic_score_gemma":0.003653993,"domain_scores_codex":[0.9994528,0.000123064,0.00002705793,0.0001824622,0.0001897891,0.00002488881],"domain_scores_gemma":[0.9994069,0.0002179801,0.00008343032,0.00008591105,0.0001882394,0.0000175379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001130119,0.0001659396,0.0049421,0.0004650874,0.0001246634,0.0001367983,0.0002450825,0.04949244,0.1164742,0.008153615,0.003197564,0.8164895],"study_design_scores_gemma":[0.00007008956,0.0004569385,0.02089755,0.00008117051,0.0001232276,0.001433358,0.0003254009,0.8722339,0.06164274,0.01852131,0.02400676,0.0002074993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003979788,0.00007217668,0.9950216,0.00003536882,0.00001454508,0.00003505495,0.00007180375,0.0003888028,0.0003808755],"genre_scores_gemma":[0.04864185,0.0001692401,0.9496264,0.00003334268,0.00002215613,0.0001082424,0.0002773237,0.00005869142,0.001062844],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002219652,"threshold_uncertainty_score":0.007425487,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2031860171","doi":"10.1080/01431160410001716923","title":"Mapping insect‐induced tree defoliation and mortality using coarse spatial resolution satellite imagery","year":2005,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":93,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Vegetation (pathology); Satellite imagery; Environmental science; Remote sensing; Spatial ecology; Satellite; Aerial imagery; Physical geography; Normalized Difference Vegetation Index; Geography; Ecology; Biology; Climate change","authors":[{"name":"Robert Fraser","is_ca":true},{"name":"R. Latifovic","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03548617583448088,"gpt":0.285096584132763,"spread":0.2496104082982821,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001650596,0.0001602509,0.00008775837,0.0004634323,0.0001766432,0.0001921489,0.0001080766,0.00009658961,0.0003590954],"category_scores_gemma":[0.0006941903,0.00007565018,0.0001013966,0.0003903786,0.0001115724,0.0001362665,0.0001066063,0.00009780126,0.00005817032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007571302,"about_ca_system_score_gemma":0.0005249159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3258061,"about_ca_topic_score_gemma":0.600625,"domain_scores_codex":[0.9999481,0.000008627643,0.000001970629,0.000009365549,0.00001829387,0.00001356927],"domain_scores_gemma":[0.9996767,0.00008270949,0.0001089036,0.00002530303,0.00007678943,0.00002960347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007756352,0.00006491227,0.9254218,0.00003419104,0.00004983,0.0001686817,0.0001907641,0.02015642,0.01216448,0.00009319577,0.0004551565,0.041123],"study_design_scores_gemma":[0.000003945332,0.00002071888,0.977186,0.000003514933,0.0000109913,0.00004567359,0.0001142402,0.02142554,0.0009399395,0.00002782516,0.0002172253,0.000004392966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986545,0.00003865755,0.0007120027,0.00001716187,6.234887e-7,0.000006100563,0.000271252,0.00001708802,0.0002826191],"genre_scores_gemma":[0.9979616,0.00003966517,0.001367612,0.000004790781,0.000001279595,0.000003475652,0.000447092,0.000001668186,0.0001727936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3258061,"threshold_uncertainty_score":0.6478195,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1968601348","doi":"10.1080/01431160903380565","title":"LiDAR mapping of canopy gaps in continuous cover forests: A comparison of canopy height model and point cloud based techniques","year":2010,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":92,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Environment Research Council; Bangor University","keywords":"Lidar; Canopy; Point cloud; Remote sensing; Environmental science; Understory; Tree canopy; Cloud cover; Meteorology; Computer science; Cloud computing; Geography","authors":[{"name":"Rachel Gaulton","is_ca":true},{"name":"Tim Malthus","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01075100997314413,"gpt":0.269214789483628,"spread":0.2584637795104838,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001004952,0.0003184598,0.000367752,0.00133399,0.0001867858,0.0007447124,0.0005989941,0.0006014991,0.0004144994],"category_scores_gemma":[0.001820684,0.0002177034,0.0002890663,0.001026645,0.0001703764,0.001209545,0.0004527732,0.0001978832,0.000202489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001872767,"about_ca_system_score_gemma":0.0003248881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003094162,"about_ca_topic_score_gemma":0.003879992,"domain_scores_codex":[0.999564,0.0001257205,0.00001998529,0.00005726693,0.0001961249,0.00003679842],"domain_scores_gemma":[0.9992095,0.0004153175,0.00007485952,0.0000696311,0.0002016809,0.00002908281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008722097,0.0003503352,0.0831631,0.0005701108,0.0002028254,0.0002979853,0.0009604628,0.06159854,0.03238543,0.002523063,0.001066961,0.816009],"study_design_scores_gemma":[0.0001185019,0.0007528608,0.08765411,0.0001770543,0.0001321726,0.001317258,0.001127648,0.8837394,0.0178505,0.002719168,0.004324287,0.00008704556],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.705777,0.00248359,0.287497,0.0001409859,0.00005135904,0.000110307,0.000272069,0.0007013046,0.002966475],"genre_scores_gemma":[0.8491544,0.000989507,0.1490073,0.00003622747,0.00001784795,0.00005062511,0.0002499784,0.00005102878,0.0004430695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003094162,"threshold_uncertainty_score":0.006152332,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2047152380","doi":"10.1080/01431160500406888","title":"Assessment of land‐cover changes related to shrimp aquaculture using remote sensing data: a case study in the Giao Thuy District, Vietnam","year":2006,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Mangrove; Deforestation (computer science); Reforestation; Aquaculture; Shrimp; Land cover; Feature (linguistics); Shrimp farming; Wetland; Environmental science; Remote sensing; Land use; Geography; Environmental resource management; Ecology; Agroforestry; Computer science; Fishery; Biology","authors":[{"name":"Martin Béland","is_ca":true},{"name":"Kalifa Goı̈ta","is_ca":true},{"name":"F. Bonn","is_ca":true},{"name":"Thi-Thanh-Hiên Pham","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03734489949515291,"gpt":0.3302010912201152,"spread":0.2928561917249623,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005054146,0.0002529554,0.0001987239,0.000684443,0.0003227831,0.0004047808,0.0003987966,0.0002882443,0.0003085459],"category_scores_gemma":[0.001160613,0.0001883415,0.0002138347,0.0008444231,0.0003718937,0.0002536903,0.0002107456,0.0001895473,0.00005210707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484288,"about_ca_system_score_gemma":0.0005915344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1339234,"about_ca_topic_score_gemma":0.1761377,"domain_scores_codex":[0.9997578,0.00007245194,0.00001846785,0.00004153849,0.00006161243,0.00004808844],"domain_scores_gemma":[0.9989033,0.0004167232,0.0002646785,0.00006200474,0.0002405955,0.0001127641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000397136,0.0006262687,0.9147524,0.000197119,0.0001450306,0.01067093,0.003435404,0.02344194,0.01157825,0.0002849745,0.0005340671,0.0339364],"study_design_scores_gemma":[0.00004146643,0.0003262001,0.9479712,0.00001867453,0.00005288787,0.001339386,0.004873761,0.03994564,0.004490246,0.00009050366,0.0008239811,0.0000260663],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996378,0.00001092506,0.0001079631,0.00001436402,6.461764e-7,0.00001291317,0.00007396073,0.000002682207,0.0001387614],"genre_scores_gemma":[0.9991837,0.00002800344,0.0004205123,0.000005855672,0.000001484402,0.00000943267,0.0001760154,0.00000140583,0.0001737049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1339234,"threshold_uncertainty_score":0.2662879,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2127211078","doi":"10.1080/01431160050144965","title":"Satellite-based mapping of Canadian boreal forest fires: Evaluation and comparison of algorithms","year":2000,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":90,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Canadian Forest Service; Environment and Climate Change Canada","funders":"","keywords":"Taiga; Remote sensing; Normalized Difference Vegetation Index; Boreal; Satellite; Environmental science; Compositing; Vegetation (pathology); Meteorology; Algorithm; Sampling (signal processing); Land cover; Pixel; Boreal ecosystem; Physical geography; Geography; Computer science; Forestry; Geology; Land use; Climate change","authors":[{"name":"Zhanqing Li","is_ca":false},{"name":"S. Nadon","is_ca":true},{"name":"J. Cihlar","is_ca":false},{"name":"B. J. Stocks","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0215647276150262,"gpt":0.2763516655805064,"spread":0.2547869379654802,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003047699,0.00124316,0.0007021072,0.0023933,0.0007633563,0.001719165,0.001419738,0.0006522692,0.001089326],"category_scores_gemma":[0.004255761,0.0003192748,0.0006092361,0.001940327,0.000299334,0.0007315291,0.0005391028,0.0004050124,0.0002668554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003712435,"about_ca_system_score_gemma":0.003193818,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.540582,"about_ca_topic_score_gemma":0.4739275,"domain_scores_codex":[0.9990024,0.0001460866,0.00007061027,0.0002380394,0.0004239308,0.0001189633],"domain_scores_gemma":[0.9978829,0.0006055456,0.0001010204,0.0001211561,0.001199328,0.00009001253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001336765,0.0003765963,0.04853128,0.0003962718,0.0009470176,0.00008323671,0.0001880967,0.3069265,0.008515144,0.000876795,0.004069545,0.6277528],"study_design_scores_gemma":[0.00009789561,0.0001290195,0.03975246,0.00003721283,0.0001679312,0.00007422965,0.0001646666,0.9534577,0.004200348,0.0001749002,0.001703513,0.00004019551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8493288,0.003502659,0.1245788,0.0003148992,0.00022997,0.0006110193,0.002982027,0.006021315,0.01243047],"genre_scores_gemma":[0.7940401,0.001104699,0.1976454,0.00009921619,0.00003632732,0.000113503,0.004304304,0.0002677785,0.002388636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.459418,"threshold_uncertainty_score":0.9242472,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2146831490","doi":"10.1080/01431161.2013.810825","title":"A hybrid pansharpening approach and multiscale object-based image analysis for mapping diseased pine and oak trees","year":2013,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of British Columbia","keywords":"Oversampling; Computer science; Artificial intelligence; Smoothing; Remote sensing; Multispectral image; Tree (set theory); Pattern recognition (psychology); Cartography; Computer vision; Geography; Mathematics","authors":[{"name":"Brian Alan Johnson","is_ca":false},{"name":"Ryutaro Tateishi","is_ca":false},{"name":"Nguyen Thanh Hoan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009457026919022348,"gpt":0.2408782023514417,"spread":0.2314211754324193,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000500572,0.0002858805,0.0003680673,0.001254161,0.0001419182,0.0002936633,0.0002951256,0.0002579742,0.0005280927],"category_scores_gemma":[0.0004302399,0.0001600237,0.0004570043,0.0005709676,0.0001896648,0.00045785,0.0002930893,0.0001881794,0.0001462746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001794178,"about_ca_system_score_gemma":0.000220073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001945589,"about_ca_topic_score_gemma":0.003118899,"domain_scores_codex":[0.9998137,0.00002195478,0.00001087012,0.00005117253,0.00008133893,0.00002107078],"domain_scores_gemma":[0.9998092,0.0000389824,0.00002363769,0.00003357902,0.00008194971,0.00001266394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001507256,0.00007433092,0.006427446,0.0001375731,0.00008376928,0.0001367692,0.0001409153,0.02702159,0.5069844,0.001060614,0.0004448499,0.4573371],"study_design_scores_gemma":[0.00001383424,0.0001481423,0.02774226,0.00001136722,0.00009832325,0.0003424782,0.00007415616,0.82522,0.1428996,0.0007945923,0.002611623,0.00004343108],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2754419,0.0003359173,0.722005,0.00005754694,0.00002121427,0.00005024223,0.00008152219,0.001129224,0.0008774957],"genre_scores_gemma":[0.6341115,0.0001667151,0.3648107,0.00003423705,0.00001624407,0.00003238029,0.0001304054,0.00004130249,0.0006564119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001945589,"threshold_uncertainty_score":0.00386858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1970500457","doi":"10.1080/0143116031000115274","title":"Analysis of Temperature Emissivity Separation (TES) algorithm applicability and sensitivity","year":2003,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":86,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"Jet Propulsion Laboratory; Fonds Québécois de la Recherche sur la Nature et les Technologies; Defence Research and Development Canada; Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey; Johns Hopkins University; National Aeronautics and Space Administration","keywords":"Emissivity; Hyperspectral imaging; Advanced Spaceborne Thermal Emission and Reflection Radiometer; Remote sensing; Radiometer; Broadband; Environmental science; Optics; Computer science; Algorithm; Geology; Physics; Digital elevation model","authors":[{"name":"Véronique Payan","is_ca":true},{"name":"Alain Royer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.006741275358777904,"gpt":0.2592648817015378,"spread":0.2525236063427599,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01099677,0.0009582133,0.0006291035,0.001668781,0.0005010649,0.001269268,0.0007763552,0.001053658,0.001008739],"category_scores_gemma":[0.06263588,0.0003094483,0.0007817526,0.001674296,0.0007361352,0.001736475,0.001757889,0.0009706176,0.000298717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006327222,"about_ca_system_score_gemma":0.0005209337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002049809,"about_ca_topic_score_gemma":0.001107316,"domain_scores_codex":[0.993576,0.002280289,0.0005927684,0.001320772,0.001877717,0.0003524116],"domain_scores_gemma":[0.9495629,0.04032974,0.001825527,0.003160591,0.00483039,0.0002907292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002653655,0.0002960022,0.1206101,0.0007749767,0.001308645,0.0004496305,0.0006271107,0.5227538,0.04152376,0.005935434,0.002820888,0.3002459],"study_design_scores_gemma":[0.00006366885,0.0005391861,0.06584509,0.00009287851,0.0002388528,0.0005953446,0.0003230794,0.8729933,0.05285619,0.003271393,0.003068381,0.0001126517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8069679,0.002302386,0.1843707,0.0003467079,0.0001626259,0.0001922007,0.000547617,0.001225505,0.003884319],"genre_scores_gemma":[0.9416828,0.0004140842,0.05539342,0.0001420558,0.00006155648,0.0001314232,0.00125642,0.0003011945,0.0006170645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01099677,"threshold_uncertainty_score":0.05815709,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1990064929","doi":"10.1080/01431160210144697","title":"Comparative analysis of daytime fire detection algorithms using AVHRR data for the 1995 fire season in Canada: Perspective for MODIS","year":2003,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Environmental science; Algorithm; Pixel; Remote sensing; Boreal; Taiga; Daytime; Meteorology; Geography; Computer science; Forestry; Atmospheric sciences; Geology; Artificial intelligence","authors":[{"name":"Charles Ichoku","is_ca":false},{"name":"Yoram J. Kaufman","is_ca":false},{"name":"Louis Giglio","is_ca":false},{"name":"Zhanqing Li","is_ca":true},{"name":"Robert Fraser","is_ca":true},{"name":"Jizhong Jin","is_ca":true},{"name":"W. M. Park","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.035035558611187,"gpt":0.3019702400989779,"spread":0.2669346814877909,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002770091,0.000804609,0.0005151532,0.001618811,0.001026056,0.001534076,0.0007061199,0.0003900827,0.0003904786],"category_scores_gemma":[0.007527248,0.0003282205,0.0006623883,0.00241834,0.0003948608,0.0006305435,0.0002877553,0.0002977273,0.0002017857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007829101,"about_ca_system_score_gemma":0.006460618,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9028223,"about_ca_topic_score_gemma":0.9322621,"domain_scores_codex":[0.9982835,0.0001977302,0.0001141911,0.000267505,0.0008970013,0.0002399501],"domain_scores_gemma":[0.9928488,0.00146838,0.0002977238,0.0001894604,0.005029708,0.0001660305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001935924,0.0001830252,0.670351,0.0006110444,0.001028607,0.0003306781,0.0009995103,0.06575581,0.01832138,0.001240812,0.003918748,0.2353233],"study_design_scores_gemma":[0.00006430024,0.0001689832,0.8656878,0.00007457266,0.0003744858,0.0001352268,0.001069122,0.1197633,0.009394285,0.0001704049,0.00301479,0.00008252655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863241,0.001302524,0.004913214,0.0001903972,0.00002385998,0.00007344873,0.001811309,0.0003475007,0.005013538],"genre_scores_gemma":[0.980431,0.0006058053,0.01346576,0.00006095534,0.000008772317,0.00002838311,0.003934327,0.0001060857,0.001358902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09717768,"threshold_uncertainty_score":0.1954999,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2738076904","doi":"10.1080/01431161.2017.1356488","title":"A comparative assessment of multi-temporal Landsat 8 and machine learning algorithms for estimating aboveground carbon stock in coppice oak forests","year":2017,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Tarbiat Modares University; Universidade de São Paulo; University of British Columbia","keywords":"Random forest; Support vector machine; Remote sensing; Environmental science; Understory; Multispectral image; Multivariate adaptive regression splines; Carbon stock; Biomass (ecology); Computer science; Climate change; Regression analysis; Machine learning; Bayesian multivariate linear regression; Canopy; Ecology; Geography","authors":[{"name":"Amir Safari","is_ca":false},{"name":"Hormoz Sohrabi","is_ca":false},{"name":"Scott Powell","is_ca":false},{"name":"Shaban Shataee","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04740792611913073,"gpt":0.3532038238105832,"spread":0.3057958976914524,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004819092,0.0006754671,0.0004846843,0.002950244,0.0002353392,0.001064536,0.0006190735,0.0007493939,0.0004340041],"category_scores_gemma":[0.004623106,0.0001716493,0.0006374482,0.001347209,0.0001891937,0.001171556,0.0003821017,0.0003011878,0.0001726375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005947321,"about_ca_system_score_gemma":0.000557982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007215634,"about_ca_topic_score_gemma":0.009235154,"domain_scores_codex":[0.9989817,0.0003434135,0.0001101839,0.0002173409,0.0002836358,0.00006379411],"domain_scores_gemma":[0.9974461,0.001396672,0.0002833471,0.0002075441,0.0005791089,0.00008732812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001834492,0.0007067695,0.1944848,0.0005417176,0.0007334522,0.0001440542,0.0002305076,0.2301765,0.01029746,0.001735483,0.001302093,0.5578127],"study_design_scores_gemma":[0.00003996558,0.0004609986,0.1286611,0.00008733974,0.0001497146,0.0001309157,0.0002842585,0.8641019,0.004024247,0.000661476,0.001346125,0.00005195621],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9373375,0.003704806,0.05449578,0.0002375398,0.00006795649,0.00006952797,0.0006046174,0.0004389658,0.003043298],"genre_scores_gemma":[0.9276404,0.001110669,0.0694478,0.00005177286,0.00003105327,0.00004012297,0.000966344,0.00005990683,0.0006518899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007215634,"threshold_uncertainty_score":0.02548611,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2030909241","doi":"10.1080/01431160902825016","title":"Global long-term monitoring of the ozone layer – a prerequisite for predictions","year":2009,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":72,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"SCIAMACHY; Environmental science; Ozone layer; Satellite; Ozone; Montreal Protocol; Meteorology; Term (time); Atmospheric sciences; Climatology; Geography; Troposphere; Geology","authors":[{"name":"Diego Loyola","is_ca":false},{"name":"R. M. Coldewey-Egbers","is_ca":false},{"name":"M. Dameris","is_ca":false},{"name":"Hella Garny","is_ca":false},{"name":"Andrea Stenke","is_ca":false},{"name":"Michel Van Roozendaël","is_ca":false},{"name":"Christophe Lerot","is_ca":false},{"name":"Dimitris Balis","is_ca":false},{"name":"Maria-Elissavet Koukouli","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0200232165860954,"gpt":0.2811263893622279,"spread":0.2611031727761325,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001530359,0.0005955518,0.0003391428,0.0008001663,0.0004196417,0.001233863,0.0006407916,0.0007099251,0.001171481],"category_scores_gemma":[0.001174005,0.0002336171,0.0003833064,0.001204895,0.0003053774,0.001980749,0.0008858544,0.0007379671,0.0007754401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138467,"about_ca_system_score_gemma":0.001662759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05241385,"about_ca_topic_score_gemma":0.05570693,"domain_scores_codex":[0.9995821,0.00007775707,0.0000316414,0.00009249648,0.0001586349,0.00005737533],"domain_scores_gemma":[0.9993905,0.00004319751,0.0001170324,0.0001301713,0.0002585819,0.00006062372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001862327,0.00033343,0.2744853,0.001054685,0.0005292977,0.0004308288,0.0002544861,0.143002,0.08716711,0.01412788,0.03070131,0.4477274],"study_design_scores_gemma":[0.00005678278,0.0003778365,0.6324142,0.0005525577,0.0003954417,0.0001581562,0.0007349398,0.1187725,0.03441098,0.02009843,0.1918056,0.0002225959],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4994168,0.05199353,0.3161934,0.01202269,0.001259134,0.001021913,0.05253264,0.003812319,0.06174755],"genre_scores_gemma":[0.8569472,0.01357033,0.09996077,0.0006852566,0.0003739209,0.0003274457,0.02250056,0.0003021377,0.00533232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05241385,"threshold_uncertainty_score":0.1042175,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2134415173","doi":"10.1080/01431160110113971","title":"Evidential reasoning with Landsat TM, DEM and GIS data for landcover classification in support of grizzly bear habitat mapping","year":2002,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Ursus; Habitat; Satellite imagery; Remote sensing; Cartography; Classifier (UML); Thematic Mapper; Grizzly Bears; Geography; Classification scheme; Computer science; Ecology; Artificial intelligence; Machine learning; Population","authors":[{"name":"Steven E. Franklin","is_ca":false},{"name":"Derek R. Peddle","is_ca":false},{"name":"Jeff A Dechka","is_ca":false},{"name":"Gordon Stenhouse","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04087773612842627,"gpt":0.2652109522293063,"spread":0.22433321610088,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01137065,0.0006115148,0.0006290186,0.001690487,0.0005735013,0.00163072,0.001484939,0.0006586114,0.001148665],"category_scores_gemma":[0.04472555,0.0002745735,0.0006247155,0.000742366,0.0005253436,0.002444487,0.001351993,0.00121,0.0004935706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004836593,"about_ca_system_score_gemma":0.0008075171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00157252,"about_ca_topic_score_gemma":0.002357068,"domain_scores_codex":[0.9964759,0.001444406,0.0005328592,0.0004551974,0.0009525623,0.0001390337],"domain_scores_gemma":[0.9726598,0.02024287,0.001904143,0.001963698,0.002961506,0.0002679827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001632071,0.0009132316,0.04857136,0.0005394858,0.0002794511,0.0007830643,0.00171736,0.151143,0.01566167,0.01464246,0.004638971,0.7594778],"study_design_scores_gemma":[0.0001118215,0.0002629862,0.006933907,0.00006125245,0.00009896448,0.0002125835,0.0001997798,0.9697939,0.007842238,0.0129717,0.001476818,0.00003398476],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2575873,0.0001597559,0.7359291,0.0004766658,0.000044009,0.0002713593,0.0003261123,0.001264137,0.003941579],"genre_scores_gemma":[0.7072064,0.00007629402,0.2912344,0.0001109117,0.00004443659,0.0001265731,0.0004430273,0.00003260207,0.0007253294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01137065,"threshold_uncertainty_score":0.06013441,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2074234119","doi":"10.1080/01431160210144606","title":"Towards an automated ocean feature detection, extraction and classification scheme for SAR imagery","year":2003,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Space Agency; National Aeronautics and Space Administration","keywords":"Computer science; Synthetic aperture radar; Feature extraction; Artificial intelligence; Feature (linguistics); Remote sensing; Pattern recognition (psychology); Wavelet; Histogram; Computer vision; Geology; Image (mathematics)","authors":[{"name":"Shuying Wu","is_ca":false},{"name":"A. K. Liu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01578557259746305,"gpt":0.2747427211017871,"spread":0.2589571485043241,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001050388,0.0006117002,0.0007170109,0.001681066,0.0004582817,0.00111787,0.001100174,0.0008305989,0.001052366],"category_scores_gemma":[0.002070335,0.0003236089,0.0005274086,0.001015971,0.0004920006,0.001059632,0.0006099946,0.0006803718,0.001327003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004192111,"about_ca_system_score_gemma":0.001087546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00387772,"about_ca_topic_score_gemma":0.004235137,"domain_scores_codex":[0.9993379,0.0001254512,0.00006867581,0.0001358072,0.000268513,0.00006377853],"domain_scores_gemma":[0.9987866,0.000231911,0.0001555895,0.0001985438,0.0005810692,0.00004629407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002007071,0.0002012664,0.002720626,0.0001024101,0.00003422897,0.00006732321,0.0001504414,0.01516608,0.1009934,0.00333066,0.003141889,0.873891],"study_design_scores_gemma":[0.0001034939,0.000356822,0.008848607,0.00004370034,0.00008210538,0.0002757888,0.0001729375,0.866509,0.1064055,0.005563983,0.01156016,0.00007797051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01713653,0.0001051529,0.9795226,0.0000924153,0.00001320857,0.0001776079,0.0001257566,0.002267734,0.0005589503],"genre_scores_gemma":[0.04735618,0.0000616984,0.9509555,0.00005094827,0.00001337416,0.0001510084,0.0003656379,0.00004238933,0.001003386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00387772,"threshold_uncertainty_score":0.007710338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2132099602","doi":"10.1080/01431160902755346","title":"The impact of imperfect ground reference data on the accuracy of land cover change estimation","year":2009,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Forest Service","keywords":"Change detection; Land cover; Ground truth; Reference data; Data set; Remote sensing; Computer science; Estimation; Cover (algebra); Set (abstract data type); Environmental science; Land use; Statistics; Data mining; Mathematics; Geography; Artificial intelligence; Ecology","authors":[{"name":"Giles M. Foody","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04958561424397102,"gpt":0.3291342431927547,"spread":0.2795486289487837,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0340075,0.0007683925,0.0009566206,0.00161228,0.0009022244,0.00206631,0.001111116,0.001149671,0.0008995476],"category_scores_gemma":[0.2215779,0.0006954753,0.00067121,0.003292735,0.002205911,0.002300238,0.001834357,0.0007986549,0.0004927698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002445935,"about_ca_system_score_gemma":0.001103852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03315834,"about_ca_topic_score_gemma":0.02158197,"domain_scores_codex":[0.9607012,0.02091406,0.002966589,0.003450773,0.01076302,0.001204206],"domain_scores_gemma":[0.7543334,0.1919125,0.01431924,0.02076595,0.01820707,0.0004617378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001513921,0.0001471484,0.5161225,0.001301371,0.000800014,0.0006363522,0.001975904,0.2611074,0.01191058,0.007122781,0.002648794,0.1947133],"study_design_scores_gemma":[0.0001022386,0.0006987234,0.7660467,0.0004911636,0.0004755981,0.001353457,0.001178742,0.1657632,0.0389092,0.01149101,0.01322093,0.000269111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7800555,0.006914632,0.1919948,0.00230979,0.0003414783,0.0003118397,0.00295998,0.0007674895,0.0143445],"genre_scores_gemma":[0.9745286,0.0005709809,0.02301813,0.0002326558,0.00003542093,0.00005108304,0.0009593794,0.00009571259,0.0005080309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0340075,"threshold_uncertainty_score":0.179851,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2120429645","doi":"10.1080/01431160600821010","title":"Validation of chlorophyll fluorescence derived from MERIS on the west coast of Canada","year":2007,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Fisheries and Oceans Canada","funders":"University of Washington; Canadian Space Agency; National Oceanic and Atmospheric Administration; University of British Columbia; Fisheries and Oceans Canada; San Francisco State University","keywords":"Radiance; Remote sensing; Environmental science; Chlorophyll a; Buoy; Satellite; Chlorophyll; Chlorophyll fluorescence; Absorption (acoustics); Fluorescence; Atmosphere (unit); Chemistry; Geology; Physics; Meteorology; Oceanography; Optics; Astronomy","authors":[{"name":"J.F.R. Gower","is_ca":true},{"name":"Stephanie King","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0109114118168851,"gpt":0.2045965083093395,"spread":0.1936850964924544,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001009417,0.0007550005,0.0003440183,0.0008547597,0.001335633,0.0009146268,0.000949806,0.0004371212,0.0007611075],"category_scores_gemma":[0.002374233,0.0002859012,0.0003899779,0.001159449,0.0004278241,0.0005161891,0.0005030346,0.0004190842,0.0003770735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0068588,"about_ca_system_score_gemma":0.006510688,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9458883,"about_ca_topic_score_gemma":0.9661746,"domain_scores_codex":[0.9991776,0.00004835809,0.00002803512,0.0002135279,0.0003647405,0.0001677906],"domain_scores_gemma":[0.9982634,0.0001085597,0.0000781042,0.0001037127,0.001323028,0.0001231988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00102408,0.0003018341,0.7875777,0.0002138982,0.0003485348,0.0003897794,0.001158428,0.04191022,0.08157304,0.000927011,0.006564105,0.07801127],"study_design_scores_gemma":[0.00008561202,0.00006546509,0.9298897,0.00005690853,0.00005224736,0.00005584754,0.0004952737,0.04931821,0.01516768,0.00008535002,0.004680899,0.000046733],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900101,0.000145007,0.001206296,0.00008163404,0.00002062377,0.00003336655,0.003908592,0.0002318579,0.004362389],"genre_scores_gemma":[0.9878833,0.0001086294,0.003096829,0.00005894116,0.000004368382,0.00002147259,0.007397361,0.00005207536,0.001377117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05411166,"threshold_uncertainty_score":0.1088606,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2099867025","doi":"10.1080/01431160701311291","title":"Improved topographic correction of forest image data using a 3‐D canopy reflectance model in multiple forward mode","year":2007,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Canadian Forest Service; University of Lethbridge","funders":"","keywords":"Terrain; Remote sensing; Canopy; Scale (ratio); Pixel; Bidirectional reflectance distribution function; Vegetation (pathology); Tree canopy; Geology; Reflectivity; Environmental science; Geography; Cartography; Physics; Optics","authors":[{"name":"Scott Soenen","is_ca":true},{"name":"Derek R. Peddle","is_ca":true},{"name":"Craig A. Coburn","is_ca":true},{"name":"Ronald J. Hall","is_ca":true},{"name":"F. G. HALL","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02956448803068986,"gpt":0.3160503694935734,"spread":0.2864858814628836,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002884502,0.0003889042,0.0002958206,0.0003615711,0.000223133,0.0004906658,0.0005318145,0.0002794717,0.000659372],"category_scores_gemma":[0.0006888873,0.0002129444,0.000423432,0.0005081773,0.0001517128,0.0003742533,0.000289618,0.0004080937,0.0003289949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005725226,"about_ca_system_score_gemma":0.001245275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05851288,"about_ca_topic_score_gemma":0.1045758,"domain_scores_codex":[0.9998704,0.00001347855,0.000005178714,0.00003261796,0.00006494451,0.00001338099],"domain_scores_gemma":[0.9998465,0.00003012367,0.00002055577,0.00002856435,0.00006667549,0.000007671349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001290598,0.00007937575,0.01221036,0.00008119534,0.00006318286,0.0001209755,0.0001587841,0.6621091,0.05886098,0.001199279,0.002005636,0.2629821],"study_design_scores_gemma":[0.000009875286,0.00001258648,0.006074936,0.000003027972,0.000008430605,0.00003107191,0.00001315103,0.9896281,0.003214036,0.0001691955,0.0008193291,0.00001634814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3248253,0.0002032026,0.66699,0.0001870919,0.00007082271,0.00007190419,0.0005831691,0.004534727,0.002533859],"genre_scores_gemma":[0.7612916,0.0001152912,0.2352295,0.00004895095,0.00001483929,0.00004191752,0.0007474933,0.0002186655,0.002291579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05851288,"threshold_uncertainty_score":0.1163446,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2035179364","doi":"10.1080/01431161.2010.483485","title":"Evaluation of soil moisture derived from passive microwave remote sensing over agricultural sites in Canada using ground-based soil moisture monitoring networks","year":2010,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"","keywords":"Environmental science; Water content; Remote sensing; Radiometer; Atmospheric sciences; Meteorology; Geology; Geography","authors":[{"name":"Catherine Champagne","is_ca":true},{"name":"Aaron Berg","is_ca":true},{"name":"Jon Belanger","is_ca":true},{"name":"Heather McNairn","is_ca":true},{"name":"Richard de Jeu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01423069453544264,"gpt":0.2459295297590031,"spread":0.2316988352235604,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006674582,0.0005960444,0.0002787636,0.0008717959,0.0007304105,0.0007539636,0.0008200441,0.0002460796,0.0004873161],"category_scores_gemma":[0.002013859,0.0002297568,0.0002926591,0.001845967,0.0002993591,0.00050094,0.0003833338,0.0002542291,0.000117968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01178634,"about_ca_system_score_gemma":0.005859153,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9818539,"about_ca_topic_score_gemma":0.9888588,"domain_scores_codex":[0.9995884,0.00003131725,0.00002050673,0.00009832777,0.000183937,0.0000774403],"domain_scores_gemma":[0.9988335,0.0001240889,0.00008758088,0.00005576155,0.0008138929,0.00008514728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006793044,0.000236595,0.8166283,0.0002662863,0.0003601638,0.0003016756,0.0006016688,0.07369724,0.01915821,0.0006186907,0.003205454,0.08424654],"study_design_scores_gemma":[0.00005494704,0.00006001533,0.9149082,0.00002642988,0.00009095265,0.00004486944,0.0005397914,0.07717022,0.004274932,0.00005909231,0.002732001,0.00003852375],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936157,0.0001025448,0.000705111,0.00004835047,0.000003816914,0.00003571667,0.00424601,0.00009502626,0.001147623],"genre_scores_gemma":[0.9874249,0.0001369841,0.002673462,0.00002545356,0.000002697206,0.00002001674,0.008996003,0.00001891263,0.0007015957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0181461,"threshold_uncertainty_score":0.08551627,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2523609223","doi":"10.1080/01431161.2016.1219425","title":"Updating residual stem volume estimates using ALS- and UAV-acquired stereo-photogrammetric point clouds","year":2016,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of British Columbia","funders":"","keywords":"Point cloud; Forest inventory; Photogrammetry; Environmental science; Residual; Volume (thermodynamics); Remote sensing; Mean squared error; Laser scanning; Diameter at breast height; Lidar; Forest management; Forestry; Computer science; Mathematics; Statistics; Geography; Agroforestry; Computer vision; Algorithm","authors":[{"name":"Tristan R.H. Goodbody","is_ca":true},{"name":"Nicholas C. Coops","is_ca":true},{"name":"Piotr Tompalski","is_ca":true},{"name":"Shane Crawford","is_ca":false},{"name":"Ken J. K. Day","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02075346862352886,"gpt":0.2713253923537878,"spread":0.2505719237302589,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003968802,0.0006303146,0.0003318846,0.001432056,0.0003028287,0.001077088,0.001029017,0.0002880503,0.0006788795],"category_scores_gemma":[0.001171068,0.000373437,0.0005497241,0.001252155,0.0001961916,0.0009427912,0.000480089,0.0003131432,0.0003690802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001525335,"about_ca_system_score_gemma":0.001557419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1380743,"about_ca_topic_score_gemma":0.2316304,"domain_scores_codex":[0.9997104,0.00001895051,0.00001488112,0.00008624289,0.0001310031,0.00003857521],"domain_scores_gemma":[0.9993778,0.0000935261,0.0001070956,0.00008873438,0.0003073489,0.00002542294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001083969,0.0001375912,0.1456403,0.00006779459,0.0001066375,0.00009127859,0.000196356,0.7064835,0.009192999,0.0005155368,0.001151474,0.1363082],"study_design_scores_gemma":[0.00001011294,0.00002603638,0.03842369,0.00001280856,0.00002160669,0.00002333751,0.00008105883,0.9569885,0.003296492,0.0002771787,0.0008165556,0.00002264634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8656096,0.0002437031,0.1243979,0.0000689031,0.00003247587,0.0001341718,0.003255955,0.002479762,0.00377752],"genre_scores_gemma":[0.9508539,0.00008225626,0.04605069,0.00001533867,0.000006713096,0.0000419733,0.002388192,0.00006921389,0.0004917471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1380743,"threshold_uncertainty_score":0.2745413,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2000299034","doi":"10.1080/01431160310001642296","title":"Contextual classification of Landsat TM images to forest inventory cover types","year":2004,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":58,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Smoothing; Random forest; Spatial contextual awareness; Pattern recognition (psychology); Pixel; Spatial analysis; Computer science; Classifier (UML); Statistics; Land cover; Remote sensing; Artificial intelligence; Mathematics; Geography","authors":[{"name":"Steen Magnussen","is_ca":true},{"name":"Paul Boudewyn","is_ca":true},{"name":"Michael A. Wulder","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01361122644622987,"gpt":0.2542831986349662,"spread":0.2406719721887364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008564183,0.0004670753,0.0003261903,0.0009243027,0.0003337971,0.0004951716,0.0002724786,0.0002231532,0.00118038],"category_scores_gemma":[0.003846938,0.0001257168,0.0004969562,0.0008703719,0.0002612426,0.0004946841,0.0006080504,0.0002925427,0.0004100351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004446554,"about_ca_system_score_gemma":0.0004029223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01038255,"about_ca_topic_score_gemma":0.02154343,"domain_scores_codex":[0.999532,0.0001105613,0.00002821213,0.0001418404,0.0001197835,0.00006763441],"domain_scores_gemma":[0.9984428,0.0003477419,0.0002324661,0.0002238425,0.0006907589,0.0000623299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001692282,0.0002813635,0.2533869,0.0004183479,0.000285584,0.0001068793,0.0004677691,0.08569348,0.06351817,0.001484264,0.003902486,0.5887624],"study_design_scores_gemma":[0.00006711375,0.0007924492,0.4722619,0.0001206561,0.0003415625,0.0002570981,0.000721816,0.480678,0.03682772,0.0029541,0.004870254,0.0001073987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9040993,0.0005602803,0.08981252,0.00007777398,0.00004460072,0.0001780668,0.001102413,0.001055881,0.003069133],"genre_scores_gemma":[0.953664,0.0001038973,0.04466034,0.00002738903,0.00002922474,0.00005400269,0.001052163,0.00003767196,0.0003712551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01038255,"threshold_uncertainty_score":0.02064425,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2172113778","doi":"10.1080/01431160110113917","title":"A multivariate approach to vegetation mapping of Manitoba's Hudson Bay Lowlands","year":2002,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":58,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Churchill Northern Studies Centre; National Park Service; Natural Sciences and Engineering Research Council of Canada; Fisheries and Oceans Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Parks Canada","keywords":"Vegetation (pathology); Vegetation classification; Bay; Remote sensing; Geography; Physical geography; Principal component analysis; Multivariate statistics; Cartography; Environmental science; Computer science","authors":[{"name":"Ryan K. Brook","is_ca":false},{"name":"N. C. Kenkel","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02332417593305457,"gpt":0.2336245271153178,"spread":0.2103003511822632,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002283847,0.000259443,0.0001417671,0.001409512,0.0005399876,0.0005292216,0.0002979695,0.00006732766,0.001024349],"category_scores_gemma":[0.0006187066,0.0001178647,0.0001521933,0.00177315,0.0001847633,0.0001417817,0.0003611333,0.0002180744,0.00006963138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001162481,"about_ca_system_score_gemma":0.001325704,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3217926,"about_ca_topic_score_gemma":0.6803969,"domain_scores_codex":[0.9999113,0.00002527891,0.000003705075,0.00002701835,0.00001787768,0.00001481763],"domain_scores_gemma":[0.9998447,0.00003646982,0.00002328654,0.00001527837,0.00006087407,0.00001943788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002097169,0.0001586128,0.5167879,0.000157523,0.0001912009,0.0004061333,0.002588501,0.01878461,0.02031232,0.003085391,0.002965191,0.4343529],"study_design_scores_gemma":[0.00001211436,0.0000558408,0.9078574,0.00003410717,0.00005663914,0.0001775287,0.003634658,0.07432733,0.002217772,0.001998002,0.009602468,0.00002607398],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9170173,0.0005541154,0.07460634,0.0003286096,0.00002173102,0.0001021776,0.001750201,0.000201635,0.005417855],"genre_scores_gemma":[0.9372959,0.0002347799,0.05947578,0.00002354819,0.000008093563,0.0000725529,0.0006680968,0.00002871897,0.002192686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6782074,"threshold_uncertainty_score":0.6398392,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1982719377","doi":"10.1080/01431161.2015.1029099","title":"A new method to generate a high-resolution global distribution map of lake chlorophyll","year":2015,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":54,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"European Space Agency; Michigan Technological University; U.S. Geological Survey; National Aeronautics and Space Administration","keywords":"Environmental science; Chlorophyll a; Remote sensing; Satellite; Satellite imagery; Range (aeronautics); Geology","authors":[{"name":"Michael J. Sayers","is_ca":false},{"name":"Amanda G. Grimm","is_ca":false},{"name":"Robert A. Shuchman","is_ca":false},{"name":"Andrew M. Deines","is_ca":false},{"name":"David B. Bunnell","is_ca":false},{"name":"Zachary B. Raymer","is_ca":false},{"name":"Mark W. Rogers","is_ca":false},{"name":"Whitney M. Woelmer","is_ca":false},{"name":"David H. Bennion","is_ca":false},{"name":"Colin Brooks","is_ca":false},{"name":"M. A. Whitley","is_ca":false},{"name":"David M. Warner","is_ca":false},{"name":"Justin G. Mychek‐Londer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01846928080752369,"gpt":0.2652749105430059,"spread":0.2468056297354823,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000331847,0.0005731917,0.0003178456,0.001689626,0.0003043349,0.0007081615,0.0004854943,0.0003789542,0.003584927],"category_scores_gemma":[0.000745165,0.0004126461,0.0007219927,0.001492719,0.0001409643,0.0006501265,0.0006671043,0.0004724219,0.001359487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003745181,"about_ca_system_score_gemma":0.0007532369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008630932,"about_ca_topic_score_gemma":0.01139315,"domain_scores_codex":[0.9998203,0.00001141638,0.000008575251,0.00007548383,0.00006261782,0.00002165259],"domain_scores_gemma":[0.9997961,0.0000310438,0.00002122941,0.00003240591,0.0001075347,0.00001177351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001409097,0.0001201054,0.0155421,0.0002129827,0.0002529575,0.0002736066,0.0002224655,0.1025216,0.07252624,0.002610466,0.01483234,0.7907443],"study_design_scores_gemma":[0.00007852265,0.00006065226,0.01994664,0.00001758827,0.00006476948,0.0002100393,0.00007699934,0.9315146,0.02329491,0.002210522,0.02246529,0.00005962522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04450139,0.0001139474,0.9395123,0.00009396931,0.00007474445,0.0001565512,0.00328534,0.009961856,0.00229995],"genre_scores_gemma":[0.1450147,0.00009167496,0.8449104,0.00005233764,0.00003343098,0.0002946536,0.006401098,0.0007649094,0.002436663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008630932,"threshold_uncertainty_score":0.01716137,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1985338631","doi":"10.1080/01431160410001726030","title":"DSM generation and evaluation from QuickBird stereo imagery with 3D physical modelling","year":2004,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Natural Resources Canada","funders":"Natural Resources Canada","keywords":"Digital elevation model; Photogrammetry; Elevation (ballistics); Remote sensing; Lidar; Terrain; Land cover; Digital surface; Scale (ratio); Data set; Computer science; Geology; Geography; Artificial intelligence; Cartography; Land use; Mathematics","authors":[{"name":"Thierry Toutin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02428163696854597,"gpt":0.2731325074385308,"spread":0.2488508704699848,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001631438,0.0009364608,0.0005286358,0.002102862,0.000380439,0.001081745,0.001102033,0.0006108007,0.00276951],"category_scores_gemma":[0.00315303,0.0003733483,0.000737922,0.001329559,0.000243212,0.0005040515,0.0006765992,0.0002858369,0.001037303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007639079,"about_ca_system_score_gemma":0.0007545358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02020846,"about_ca_topic_score_gemma":0.01515993,"domain_scores_codex":[0.9994282,0.0001342859,0.00003960865,0.00004800501,0.0002926493,0.00005734751],"domain_scores_gemma":[0.9987442,0.0002152965,0.00005808225,0.0001927194,0.0007202831,0.00006933659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001223476,0.0006254059,0.01400347,0.0007660964,0.0002283888,0.0005693047,0.000382646,0.696463,0.02339296,0.001697278,0.006367169,0.2542807],"study_design_scores_gemma":[0.0001549806,0.0001411976,0.00926707,0.00003370123,0.00004388006,0.00009113063,0.0001548944,0.9780724,0.009238155,0.0004220602,0.002340926,0.00003965465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7874326,0.0005375926,0.1760138,0.0003347384,0.0003089104,0.001673022,0.01170445,0.008777091,0.01321792],"genre_scores_gemma":[0.837727,0.0002353226,0.1522179,0.00005803378,0.00002266502,0.0002535409,0.007892434,0.0003969637,0.001196054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02020846,"threshold_uncertainty_score":0.04018164,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4233199126","doi":"10.1080/01431160120291","title":"Multitemporal monitoring of soil moisture with RADARSAT SAR during the 1997 Southern Great Plains hydrology experiment","year":2001,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Space Agency; University of Bath; National Aeronautics and Space Administration; U.S. Department of Energy","keywords":"Hydrology (agriculture); Environmental science; Water content; Geology; Remote sensing","authors":[{"name":"A. J. Wickel","is_ca":false},{"name":"Thomas J. Jackson","is_ca":false},{"name":"E. F. Wood","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009195638982366883,"gpt":0.2365283651045597,"spread":0.2273327261221928,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000447332,0.0002635527,0.0002780225,0.000264854,0.0004318914,0.0003479102,0.0002716836,0.0004142917,0.0004075613],"category_scores_gemma":[0.0004843973,0.0002014076,0.0001255785,0.0004076256,0.0004858278,0.0004188727,0.000426586,0.0003237419,0.00009905964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007592624,"about_ca_system_score_gemma":0.0006188249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06232338,"about_ca_topic_score_gemma":0.1751169,"domain_scores_codex":[0.9998813,0.0000278799,0.000006892339,0.0000287658,0.00003032563,0.0000248756],"domain_scores_gemma":[0.99958,0.00006656122,0.0001200583,0.00006155191,0.00006245268,0.0001093531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002506475,0.001785956,0.9213187,0.00003735632,0.0002978483,0.0007209845,0.001405888,0.005205205,0.05290357,0.0002831543,0.002654511,0.01088035],"study_design_scores_gemma":[0.00004107113,0.00007850282,0.9970397,8.873749e-7,0.00001675127,0.00002232477,0.0001339705,0.00143478,0.0008782864,0.0000212253,0.0003284695,0.000003923235],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999613,0.000005512135,0.0000316498,0.00002687483,0.000001732708,0.000003397016,0.0001963054,0.000006264882,0.0001152798],"genre_scores_gemma":[0.9985908,0.00001733393,0.0001893261,0.00002297575,0.000004001766,0.00001622375,0.0008082315,0.000003728833,0.0003473208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06232338,"threshold_uncertainty_score":0.1239213,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2626876192","doi":"10.1080/01431161.2017.1339920","title":"Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region","year":2017,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Erasmus+; National Oceanic and Atmospheric Administration; National Aeronautics and Space Administration","keywords":"Shrubland; Normalized Difference Vegetation Index; Environmental science; Deciduous; Vegetation (pathology); Grassland; Water content; Arid; Enhanced vegetation index; Climate change; Hydrology (agriculture); Physical geography; Geography; Ecosystem; Ecology; Vegetation Index; Geology","authors":[{"name":"Mohamed Ahmed","is_ca":true},{"name":"Brent Else","is_ca":true},{"name":"Lars Eklundh","is_ca":false},{"name":"Jonas Ardö","is_ca":false},{"name":"Jonathan Seaquist","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009881271481866304,"gpt":0.2453477900838221,"spread":0.2354665186019558,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003420535,0.0001641122,0.0001843884,0.0006028417,0.0001950553,0.0005514225,0.0001842218,0.0002188511,0.0005663171],"category_scores_gemma":[0.001174227,0.0001258789,0.0001745791,0.0007635858,0.0001925144,0.0002933846,0.000262898,0.0001906942,0.00009708698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003230236,"about_ca_system_score_gemma":0.0001945219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01450134,"about_ca_topic_score_gemma":0.01112587,"domain_scores_codex":[0.9998747,0.00003026455,0.000009098228,0.00003386196,0.0000160845,0.00003600946],"domain_scores_gemma":[0.9996531,0.0001276173,0.00008332983,0.00002347464,0.00005877401,0.0000537586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002388458,0.00006541448,0.9718635,0.00004299583,0.0001601728,0.0003934795,0.0006952092,0.004883111,0.00999531,0.0002185771,0.0003239007,0.01111945],"study_design_scores_gemma":[0.000005533678,0.00001762316,0.9929093,0.000006332974,0.00001326534,0.00004728484,0.0003208327,0.005911138,0.0004149669,0.00004697919,0.0003007588,0.000005956511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994122,0.00004468606,0.0001070721,0.00002113524,0.000002767724,0.000001600375,0.0001673872,0.000006971223,0.0002362741],"genre_scores_gemma":[0.9995732,0.00002554936,0.00008855751,0.000006623248,0.000002546022,0.000001804545,0.0002575528,0.000002141859,0.00004209947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01450134,"threshold_uncertainty_score":0.02883387,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1996347147","doi":"10.1080/01431160701281023","title":"Canopy chlorophyll concentration estimation using hyperspectral and lidar data for a boreal mixedwood forest in northern Ontario, Canada","year":2007,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Ontario Forest Research Institute; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Foundation for Climate and Atmospheric Sciences","keywords":"Hyperspectral imaging; Lidar; Environmental science; Canopy; Remote sensing; Chlorophyll; Chlorophyll a; Mean squared error; Mathematics; Geography; Botany; Biology; Statistics","authors":[{"name":"Valerie A. Thomas","is_ca":true},{"name":"Paul Treitz","is_ca":true},{"name":"J. H. McCaughey","is_ca":true},{"name":"Thomas L. Noland","is_ca":true},{"name":"L. Rich","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01378111963721008,"gpt":0.2479642830552785,"spread":0.2341831634180684,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001792213,0.0002749709,0.0002004302,0.0006095524,0.001224033,0.0006631173,0.0004722805,0.0001918666,0.000546805],"category_scores_gemma":[0.0004615097,0.0001855039,0.0001459186,0.0009724712,0.0003003574,0.0002535554,0.0002627095,0.0001866919,0.0001086264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01101481,"about_ca_system_score_gemma":0.00680885,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9885853,"about_ca_topic_score_gemma":0.9965449,"domain_scores_codex":[0.9998317,0.000007299895,0.00000583451,0.00003576724,0.00007769767,0.00004166424],"domain_scores_gemma":[0.9997179,0.00002333714,0.00002571371,0.0000080811,0.0001854718,0.00003948156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003218239,0.0001530263,0.9085923,0.0001090328,0.0000800853,0.0006567004,0.001780477,0.006923011,0.02799628,0.0002866751,0.00150925,0.05159146],"study_design_scores_gemma":[0.00002193044,0.00002190696,0.9787816,0.00001685112,0.00002722699,0.00007912653,0.001506895,0.01621567,0.001554293,0.00004288926,0.001710562,0.00002105268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977409,0.0001172169,0.0003518913,0.00003548764,0.000001933894,0.00001588217,0.0004257043,0.00002224465,0.001288779],"genre_scores_gemma":[0.9969903,0.00009131688,0.001346359,0.00001862295,0.000001264642,0.00000692692,0.0004901707,0.0000056464,0.001049308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01141471,"threshold_uncertainty_score":0.07991838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2003079203","doi":"10.1080/01431160152027665","title":"Multitemporal monitoring of soil moisture with RADARSAT SAR during the 1997 Southern Great Plains hydrology experiment","year":2001,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Space Agency; National Aeronautics and Space Administration; U.S. Department of Energy","keywords":"Synthetic aperture radar; Water content; Environmental science; Remote sensing; Correlation coefficient; Moisture; Hydrology (agriculture); Soil science; Geology; Meteorology; Geography; Mathematics","authors":[{"name":"A. J. Wickel","is_ca":false},{"name":"Thomas J. Jackson","is_ca":false},{"name":"Eric F. Wood","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009195638982366883,"gpt":0.2365283651045597,"spread":0.2273327261221928,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005936224,0.0002583811,0.0002033261,0.0002716864,0.0002286331,0.0002346409,0.0001812637,0.0002340129,0.0002087131],"category_scores_gemma":[0.0003918704,0.0001304387,0.0001108481,0.0003060531,0.0002227769,0.0002074198,0.0002674476,0.000184581,0.00006982568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003964919,"about_ca_system_score_gemma":0.0003204116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0129114,"about_ca_topic_score_gemma":0.03854248,"domain_scores_codex":[0.9998343,0.0000428355,0.000006590848,0.00003228573,0.00006261255,0.00002137275],"domain_scores_gemma":[0.9997078,0.00004385948,0.00008077601,0.00004114727,0.00005453686,0.00007178326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002122682,0.001145435,0.7050152,0.00008381185,0.0003029317,0.0007834907,0.0005110913,0.01705479,0.2450438,0.0001733663,0.001359678,0.02640375],"study_design_scores_gemma":[0.00007716002,0.0003889256,0.98376,0.000001710279,0.00003209173,0.00005430942,0.00006395747,0.00631095,0.008730378,0.0000217186,0.000550291,0.000008645688],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994594,0.00001105125,0.0001579176,0.00001279165,0.00000109468,0.000007970393,0.0001958125,0.00001875664,0.0001351721],"genre_scores_gemma":[0.9976599,0.00003038317,0.001006312,0.00001505289,0.000004164458,0.00002075615,0.001031113,0.000005644752,0.0002267133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0129114,"threshold_uncertainty_score":0.0256725,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3040364706","doi":"10.1080/01431161.2020.1754494","title":"Synthetic Aperture Radar (SAR) image processing for operational space-based agriculture mapping","year":2020,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Carleton University; Agriculture and Agri-Food Canada","funders":"Canadian Space Agency","keywords":"Computer science; Synthetic aperture radar; Remote sensing; Filter (signal processing); Terrain; Speckle noise; Speckle pattern; Artificial intelligence; Computer vision; Geography; Cartography","authors":[{"name":"Laura Dingle Robertson","is_ca":true},{"name":"Andrew Davidson","is_ca":true},{"name":"Heather McNairn","is_ca":true},{"name":"Mehdi Hosseini","is_ca":true},{"name":"Scott Mitchell","is_ca":true},{"name":"Diego de Abelleyra","is_ca":false},{"name":"Santiago R. Verón","is_ca":false},{"name":"Michael H. Cosh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01192523669955386,"gpt":0.230864138380482,"spread":0.2189389016809281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003207623,0.0004879568,0.0004168796,0.0009989185,0.0004208158,0.001540205,0.0005176747,0.0004917399,0.004172829],"category_scores_gemma":[0.004775623,0.0002806965,0.0005795383,0.001616135,0.0004110258,0.001382179,0.0005226356,0.0008791428,0.002057095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004491375,"about_ca_system_score_gemma":0.0009058702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002130808,"about_ca_topic_score_gemma":0.004875395,"domain_scores_codex":[0.9986588,0.0003747916,0.00009743903,0.0001425083,0.0006544396,0.0000721698],"domain_scores_gemma":[0.9954616,0.001863112,0.0004253035,0.0004659451,0.001703651,0.00008039687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002295213,0.0001837889,0.01319487,0.001037251,0.0001177051,0.0002384869,0.0005645607,0.01576711,0.1282441,0.004991984,0.01011212,0.8253185],"study_design_scores_gemma":[0.0001181387,0.002474067,0.1618375,0.00101094,0.0004433757,0.002492114,0.003934058,0.2155983,0.3081882,0.02270178,0.2808661,0.0003353958],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1802823,0.004034892,0.7821878,0.002162367,0.000508745,0.0005745681,0.001201429,0.002570538,0.02647739],"genre_scores_gemma":[0.3022923,0.0043845,0.6868753,0.0004421486,0.000122853,0.0002039214,0.001203337,0.0003510096,0.004124558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004172829,"threshold_uncertainty_score":0.01696372,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2091738548","doi":"10.1080/01431160701294653","title":"Estimating afternoon MODIS land surface temperatures (LST) based on morning MODIS overpass, location and elevation information","year":2007,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of British Columbia","funders":"Canadian Space Agency","keywords":"Environmental science; Moderate-resolution imaging spectroradiometer; Morning; Elevation (ballistics); Land cover; Climatology; Meteorology; Daytime; Atmospheric sciences; Insolation; Satellite; Remote sensing; Geography; Land use; Geology","authors":[{"name":"Nicholas C. Coops","is_ca":true},{"name":"Dennis C. Duro","is_ca":true},{"name":"Michael A. Wulder","is_ca":true},{"name":"Tao Han","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005631429169720589,"gpt":0.2298287362694661,"spread":0.2241973070997455,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003501564,0.0004518784,0.0002882127,0.0004314061,0.000424344,0.0005372349,0.0004259177,0.0002579781,0.0006577747],"category_scores_gemma":[0.001215964,0.0002546777,0.0002892265,0.0004910104,0.00008632998,0.0003268132,0.0002766623,0.0002864032,0.000371523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001198622,"about_ca_system_score_gemma":0.00185677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1947092,"about_ca_topic_score_gemma":0.4368462,"domain_scores_codex":[0.9998362,0.00002010951,0.000008357109,0.00004682336,0.00006602439,0.00002245347],"domain_scores_gemma":[0.9996789,0.00005151502,0.00003942486,0.00002993076,0.0001802958,0.00001996404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006676897,0.0002066895,0.5239913,0.0003155202,0.000263217,0.0002335615,0.001293888,0.08183705,0.1379281,0.0009954409,0.006069299,0.2461982],"study_design_scores_gemma":[0.00005483382,0.0001192703,0.7284157,0.00003577939,0.0001118131,0.00009884056,0.0004433682,0.2221437,0.03964941,0.000512751,0.008347984,0.00006671414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372933,0.0001802353,0.05137781,0.00008349856,0.0000428545,0.000150373,0.004122816,0.0008849148,0.005864172],"genre_scores_gemma":[0.8771909,0.0001274879,0.1159561,0.00002493388,0.00001172223,0.00007447234,0.00447279,0.0001341033,0.002007541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1947092,"threshold_uncertainty_score":0.3871517,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2033038277","doi":"10.1080/01431160600868474","title":"A semi‐automated approach for extracting buildings from QuickBird imagery applied to informal settlement mapping","year":2007,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Settlement (finance); Computer science; Remote sensing; Satellite; Ground truth; Software; Satellite imagery; Information extraction; High resolution; Extraction (chemistry); Image resolution; Artificial intelligence; Geology; Engineering","authors":[{"name":"Selassie Mayunga","is_ca":true},{"name":"David Coleman","is_ca":true},{"name":"Y. Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01268131899129865,"gpt":0.2616631676780507,"spread":0.248981848686752,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007139195,0.0006304819,0.0004725473,0.00193801,0.000414313,0.0006312277,0.0007061428,0.000460483,0.001283096],"category_scores_gemma":[0.001289223,0.000511322,0.0005704715,0.0009200997,0.0004163532,0.0006350641,0.0007236731,0.0003468676,0.0005468514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002478945,"about_ca_system_score_gemma":0.0006276575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003173318,"about_ca_topic_score_gemma":0.00611494,"domain_scores_codex":[0.9995344,0.0001453757,0.00002334457,0.00008851651,0.0001699378,0.00003846432],"domain_scores_gemma":[0.9992391,0.0002516234,0.00007332883,0.0001908756,0.0002138661,0.00003121031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001351852,0.000206594,0.006156994,0.0002810356,0.0001397097,0.0001711575,0.0004304762,0.06146234,0.1427255,0.002470644,0.001814763,0.7840056],"study_design_scores_gemma":[0.00005908414,0.0003662715,0.02319225,0.00003893498,0.0001042066,0.0008457631,0.0002561954,0.8467014,0.1158941,0.003139394,0.00926907,0.000133358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05507376,0.00007922857,0.9413798,0.000039297,0.00001838773,0.0001383875,0.0001762422,0.002217522,0.0008773577],"genre_scores_gemma":[0.1711488,0.00007024908,0.8275771,0.0000184263,0.000007096143,0.0001276458,0.000269643,0.00009166943,0.0006893387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003173318,"threshold_uncertainty_score":0.006309688,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2154464101","doi":"10.1080/01431160802275890","title":"The suitability of decadal image data sets for mapping tropical forest cover change in the Democratic Republic of Congo: implications for the global land survey","year":2008,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Department of Family and Community Medicine, University of Toronto; National Aeronautics and Space Administration","keywords":"Compositing; Thematic Mapper; Land cover; Remote sensing; Cloud cover; Pixel; Thematic map; Shadow (psychology); Tropics; Environmental science; Change detection; Geography; Physical geography; Satellite imagery; Cartography; Computer science; Land use; Cloud computing; Image (mathematics); Computer vision","authors":[{"name":"Erik Lindquist","is_ca":false},{"name":"Matthew C. Hansen","is_ca":false},{"name":"David P. Roy","is_ca":false},{"name":"C. O. Justice","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0883812866087391,"gpt":0.3409535497770719,"spread":0.2525722631683328,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003965412,0.0002657327,0.0001975218,0.001645028,0.0003942478,0.001845937,0.0003626609,0.0003511461,0.0005508063],"category_scores_gemma":[0.008628868,0.0001636441,0.0003879777,0.002006729,0.0002751172,0.001139116,0.0005720129,0.00040727,0.0001360151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001278408,"about_ca_system_score_gemma":0.0004871845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03535182,"about_ca_topic_score_gemma":0.07331388,"domain_scores_codex":[0.9988889,0.0006190066,0.00009005182,0.0001637499,0.0001374367,0.0001009267],"domain_scores_gemma":[0.9969935,0.001306828,0.0005566077,0.0004767011,0.0004789529,0.0001874027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005173234,0.0001510454,0.9234413,0.000121451,0.0003746396,0.0002446839,0.0006602215,0.01104539,0.008542405,0.0006508901,0.0008082505,0.05344241],"study_design_scores_gemma":[0.00001589363,0.00004578154,0.9852959,0.00004976967,0.00007014546,0.00008760761,0.0008917885,0.009922851,0.001172309,0.0001678413,0.002257371,0.0000227232],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943165,0.000582727,0.001011417,0.0004969545,0.00001455882,0.0000380802,0.002274374,0.0000264094,0.001238887],"genre_scores_gemma":[0.9959134,0.0002042472,0.002482994,0.00004220317,0.00001024483,0.00003534833,0.00111806,0.00001264279,0.0001808333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03535182,"threshold_uncertainty_score":0.07029206,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1989382930","doi":"10.1080/01431160310001592445","title":"On the potential of MODIS and MERIS for imaging chlorophyll fluorescence from space","year":2004,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Golder Associates (Canada)","funders":"Fisheries and Oceans Canada; Canadian Space Agency","keywords":"Imaging spectrometer; Radiance; Remote sensing; Moderate-resolution imaging spectroradiometer; Environmental science; Spectrometer; Zenith; Chlorophyll fluorescence; Solar zenith angle; Satellite; Optics; Physics; Fluorescence; Geology","authors":[{"name":"J.F.R. Gower","is_ca":false},{"name":"Gary A. Borstad","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.007070344280444816,"gpt":0.2040825427534455,"spread":0.1970121984730007,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005599387,0.0007492348,0.000512265,0.0009141925,0.0003993128,0.001674721,0.0008867794,0.0008638502,0.003030894],"category_scores_gemma":[0.005912224,0.0003874623,0.0004606573,0.001081917,0.0006489717,0.002679431,0.0009976242,0.0006210148,0.0009786922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006904527,"about_ca_system_score_gemma":0.0005338264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002382196,"about_ca_topic_score_gemma":0.003745863,"domain_scores_codex":[0.9991288,0.0002916699,0.00002419748,0.0001266812,0.0003868578,0.00004192393],"domain_scores_gemma":[0.9971161,0.001164648,0.0001260384,0.0005001103,0.0009419168,0.0001512511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001721653,0.0001789853,0.02337088,0.0008026347,0.0002134412,0.0003388833,0.0004694545,0.0201776,0.07086331,0.06692205,0.02497645,0.7899647],"study_design_scores_gemma":[0.0003138595,0.002106396,0.04179738,0.001129862,0.0005542049,0.002900471,0.0008680341,0.227671,0.1194718,0.08529937,0.5173136,0.0005741143],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3131454,0.07204511,0.3516492,0.02735171,0.001991321,0.0004885259,0.004648271,0.005791472,0.222889],"genre_scores_gemma":[0.5363721,0.0203703,0.4165617,0.002094414,0.0008197495,0.0002241554,0.001693887,0.0005585823,0.02130526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005599387,"threshold_uncertainty_score":0.02961278,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}