{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":511,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":511,"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"},"query_hash":"c5a741c3e404","filters":{"topic":"Remote Sensing and Land Use"}},"results":[{"id":"W4245972137","doi":"10.1017/9781139016476","title":"Urban Climates","year":2017,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":1426,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University; University of British Columbia","funders":"","keywords":"Urban climate; Environmental planning; Terminology; Urban design; Urban heat island; Urban planning; Resource (disambiguation); Urban climatology; Environmental resource management; Geography; Environmental science; Architectural engineering; Civil engineering; Engineering; Meteorology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02088721430705725,"gpt":0.1850916212773838,"spread":0.1642044069703266,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009990868,0.0002857752,0.0003489844,0.0001047762,0.0005103595,0.0001569837,0.0006279048,0.0003274621,0.00001987095],"category_scores_gemma":[0.00001403111,0.0002750355,0.0001769986,0.000004492543,0.000239077,0.0000979324,0.00005368591,0.0003938811,0.0001466388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002085424,"about_ca_system_score_gemma":0.0002016781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002021583,"about_ca_topic_score_gemma":0.00008400685,"domain_scores_codex":[0.9988486,0.00005445049,0.0001171239,0.0004148927,0.000223378,0.0003416096],"domain_scores_gemma":[0.9987651,0.00008088284,0.0002177442,0.0006674543,0.00006124799,0.0002076179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007724296,0.000003354992,0.0005116198,0.00008224449,0.00008847952,0.0006845067,0.00003961598,0.000006902473,9.857591e-7,0.006731972,0.9736828,0.01809028],"study_design_scores_gemma":[0.0002657521,0.00004358579,0.001854348,0.000126397,0.000112027,0.00002186412,0.0000110645,0.0004808739,0.00001473999,0.000002769663,0.9967091,0.0003574976],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000590184,0.0002933965,0.00000790867,0.000009144246,0.0005750019,0.0001566771,0.0005432328,0.0001247277,0.9976997],"genre_scores_gemma":[0.00130439,0.0001948097,0.00005427442,0.00004520105,0.0003873534,5.846167e-9,0.0004765205,0.00001018777,0.9975272],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02302628,"threshold_uncertainty_score":0.9999702,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391191157","doi":"10.5194/bg-8-489-2011","title":"An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe","year":2011,"lang":"en","type":"article","venue":"Biogeosciences","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":224,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Pelagic zone; Primary productivity; Productivity; Oceanography; Globe; Environmental science; Ocean color; Climatology; Geography; Geology; Ecosystem; Ecology; Biology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.05410749945958798,"gpt":0.2684622775060228,"spread":0.2143547780464348,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001855346,0.00006691911,0.0001163842,0.00004183919,0.0001295571,0.00001902101,0.000160638,0.00002815276,0.00001645218],"category_scores_gemma":[0.0001080924,0.000038127,0.00001668727,0.0002647444,0.0005836174,0.0002296233,0.00001967835,0.00004771146,5.141968e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001789422,"about_ca_system_score_gemma":0.0001007139,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02121372,"about_ca_topic_score_gemma":0.026668,"domain_scores_codex":[0.9990937,0.0001133649,0.0001492206,0.0001986857,0.0002963518,0.0001486922],"domain_scores_gemma":[0.999565,0.00006014824,0.0001002059,0.000158813,0.0000765309,0.00003929112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003916948,0.00005807179,0.9575787,0.00001106608,0.00000221696,4.909013e-7,0.002694372,0.001703784,0.0003585345,0.00001855953,0.000007663337,0.03752737],"study_design_scores_gemma":[0.00009111511,0.0001322767,0.6936784,0.000007337,0.000008639226,0.000005521325,0.0005849567,0.3026543,0.0005277117,0.002265831,0.000003233281,0.00004068503],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99813,0.00009680953,0.00003732352,0.00007062385,0.00006605172,0.0001512195,0.0000594001,0.000007483791,0.001381056],"genre_scores_gemma":[0.9983462,0.00003054625,0.001570552,0.00001061217,0.00001172446,9.920765e-8,0.00001791955,8.878271e-7,0.00001144869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3009506,"threshold_uncertainty_score":0.9910927,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W627818147","doi":"10.1201/9781420009781","title":"Color Image Processing","year":2006,"lang":"en","type":"book","venue":"Image processing series","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":161,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Image processing; Computer graphics (images); Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.009140786485489204,"gpt":0.215806921357748,"spread":0.2066661348722587,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002683167,0.0006742086,0.0006992585,0.000221216,0.0007826466,0.001589405,0.0004184021,0.0004334577,0.0004891028],"category_scores_gemma":[0.00006806305,0.0005528073,0.0001614019,0.0002249315,0.0006834141,0.001449222,0.00002921033,0.0006658169,0.0005344442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002947499,"about_ca_system_score_gemma":0.00111391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003929418,"about_ca_topic_score_gemma":0.001167528,"domain_scores_codex":[0.9972298,0.00005889634,0.000573698,0.0007945421,0.000598316,0.0007447614],"domain_scores_gemma":[0.9985908,0.00006254717,0.0004981085,0.0003461641,0.0003253151,0.0001770286],"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":[0.0002539765,0.00004249851,0.0005646695,0.002954855,0.00004622492,0.0007431619,0.0008048444,0.0001065315,0.0002616241,0.00001620442,0.1980748,0.7961306],"study_design_scores_gemma":[0.0005799492,0.0002368422,0.00299625,0.001923528,0.0002358104,0.0005106233,0.0001590337,0.007428999,0.0004709699,0.006852927,0.9767494,0.001855717],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001304521,0.006166016,0.0004663076,0.0004113997,0.0004371517,0.0002976374,0.0001920563,0.0005935163,0.9901314],"genre_scores_gemma":[0.003722325,0.0001199475,0.02747065,0.000308567,0.001463978,0.000001050921,0.001586477,0.00007559254,0.9652514],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7942749,"threshold_uncertainty_score":0.9996923,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2950982965","doi":"","title":"Estimating the roughness of cities and sheltered country","year":2000,"lang":"en","type":"article","venue":"Asheville Meeting","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":133,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.00927462727583444,"gpt":0.2002406677714912,"spread":0.1909660404956568,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003346227,0.00007374137,0.0001170651,0.0000155679,0.0002120781,0.00004982868,0.00008170994,0.00002763735,0.0004300567],"category_scores_gemma":[0.00005602205,0.0000438268,0.00002027823,0.00008959101,0.00008693194,0.00007225134,0.000004930817,0.00007093858,0.00001494252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":5.592458e-7,"about_ca_system_score_gemma":0.00001049418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003286024,"about_ca_topic_score_gemma":0.0004948,"domain_scores_codex":[0.9993821,0.00006175321,0.0001600483,0.0001143703,0.000128947,0.0001527209],"domain_scores_gemma":[0.9995634,0.0002247252,0.00005139876,0.000114903,0.00001519014,0.00003038436],"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":[0.00002274192,0.000003710868,0.1531023,0.00005204226,0.00001674315,0.000005762576,0.001559323,0.02562056,0.00002698333,0.00001866398,0.0001985025,0.8193727],"study_design_scores_gemma":[0.0003961488,0.00007930049,0.3300383,0.0003422241,0.00003648442,0.00008535875,0.001495459,0.6527007,0.0002377387,0.0003255641,0.01399688,0.000265755],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8982539,0.0008281766,0.00001021414,0.0001151801,0.0001041993,0.00004399109,0.000006580807,0.0000207758,0.100617],"genre_scores_gemma":[0.9974886,0.00006761553,0.001945683,0.0001177313,0.0001178365,5.435146e-8,0.000009856558,0.000002468684,0.0002502153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8191069,"threshold_uncertainty_score":0.4967507,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2032991508","doi":"10.1016/s0167-8655(99)00144-0","title":"Zernike moment-based image shape analysis and its application","year":2000,"lang":"en","type":"article","venue":"Pattern Recognition Letters","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":99,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"","keywords":"Roundness (object); Zernike polynomials; Shape analysis (program analysis); Rationality; Artificial intelligence; Computer science; Image (mathematics); Moment (physics); Image processing; Computer vision; Pattern recognition (psychology); Mathematics; Algorithm; Geometry; Optics; Static analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.01168027040805572,"gpt":0.2021982557078195,"spread":0.1905179852997637,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000107127,0.0001082765,0.0001239235,0.0001401371,0.0001035678,0.00007180968,0.00005424678,0.00003622664,0.006418855],"category_scores_gemma":[0.000003201842,0.00009444381,0.00006390613,0.0002554286,0.00002513313,0.0001243069,0.000001519756,0.00007539811,0.001221707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002867648,"about_ca_system_score_gemma":0.000003896478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008331179,"about_ca_topic_score_gemma":0.0003754842,"domain_scores_codex":[0.9992034,0.00006273444,0.0001462598,0.0002622952,0.0001466926,0.0001786447],"domain_scores_gemma":[0.9996921,0.00004801755,0.00004850877,0.0001022709,0.00001929134,0.0000898522],"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":[0.00001479265,0.000008379599,0.07888161,0.0000101331,0.00004509915,0.000007122635,0.00004293678,0.0002521361,0.0008238707,9.991439e-9,0.00007944683,0.9198345],"study_design_scores_gemma":[0.0004098953,0.00003073062,0.6694673,0.0000144105,0.0002041762,0.000006728479,0.00001224198,0.3262725,0.001252731,0.00001088143,0.002074706,0.0002436686],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926145,0.00003449228,0.004405688,0.00189603,0.00003457502,0.0001188111,0.0001194047,0.00005713978,0.0007193348],"genre_scores_gemma":[0.9929392,0.00004796186,0.0004125247,0.0053808,0.00008010251,8.906055e-7,0.001099627,0.000003704815,0.00003521336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9195908,"threshold_uncertainty_score":0.9995559,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1998513521","doi":"10.1016/0967-0653(93)94856-t","title":"10.1016/0967-0653(93)94856-t","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":85,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Radiance; Multispectral image; Thematic Mapper; Remote sensing; Change detection; Pixel; Satellite; Thematic map; Multispectral pattern recognition; Change analysis; Geography; Satellite imagery; Environmental science; Cartography; Physical geography; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.006035185696252138,"gpt":0.1495198858462652,"spread":0.143484700150013,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001248137,0.0001169363,0.0001323003,0.00004855445,0.000118119,0.00007029095,0.0001479626,0.00005525043,0.9986055],"category_scores_gemma":[0.00001732782,0.00009103721,0.00004823098,0.0001662577,0.00002620832,0.0000834114,0.000003927339,0.00009311245,0.9982499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002146572,"about_ca_system_score_gemma":0.0000191585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008255062,"about_ca_topic_score_gemma":0.0000207364,"domain_scores_codex":[0.9991598,0.00004473966,0.0001272443,0.0002087203,0.0001698554,0.0002896236],"domain_scores_gemma":[0.9995032,0.00005423952,0.00001730026,0.0002123927,0.00001658232,0.0001963097],"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":[0.00004239254,0.000006173429,0.000004699315,0.000001777406,0.000005817086,0.00001058478,0.00001760417,0.0008231922,7.761451e-7,3.719929e-8,0.1370281,0.8620589],"study_design_scores_gemma":[0.0001232688,0.0001188221,0.001947443,0.00001026067,0.000008298387,0.00002122902,0.000001325233,0.003514962,0.00001074281,0.000008927836,0.9940811,0.0001536683],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006687687,0.00009811144,3.38483e-7,0.0002402108,0.00000449111,0.00007767287,0.00002467866,0.0001049151,0.9927619],"genre_scores_gemma":[0.001797334,8.938734e-7,0.0001569743,0.0001018232,0.0001878022,7.10508e-8,0.00008493536,0.000004703124,0.9976655],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8619052,"threshold_uncertainty_score":0.371239,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2042360192","doi":"10.1007/s10661-014-3995-z","title":"Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites","year":2014,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":77,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"","keywords":"Environmental science; Satellite; Remote sensing; Municipal solid waste; Satellite imagery; Environmental monitoring; Thematic Mapper; Hydrology (agriculture); Environmental engineering; Waste management; Geology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01486686372821008,"gpt":0.2657509777102488,"spread":0.2508841139820387,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002747757,0.0001707091,0.0003735639,0.00008039334,0.000124266,0.00004040867,0.00009262675,0.00006935795,0.00001140261],"category_scores_gemma":[0.000007187246,0.0001328767,0.0001156943,0.0001024798,0.0000742003,0.00009745909,0.00002103316,0.0001177037,7.450252e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007840482,"about_ca_system_score_gemma":0.000006343837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007005815,"about_ca_topic_score_gemma":0.0000507877,"domain_scores_codex":[0.9989572,0.00007517992,0.0002745014,0.0002542002,0.0002184317,0.0002205432],"domain_scores_gemma":[0.9993883,0.0001803951,0.0001433806,0.0001823019,0.000007763558,0.00009787528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003290875,0.00004253411,0.9578842,0.00003308727,0.000190864,0.000001148867,0.0002711299,0.01000562,0.02104947,3.237124e-7,8.340439e-7,0.01048787],"study_design_scores_gemma":[0.0004765543,0.0001740544,0.9466375,0.00004909067,0.0002332264,9.406814e-7,0.0008148663,0.02559726,0.02574843,0.000003850634,0.0001152745,0.0001490278],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983354,0.0009940215,0.00007910423,0.00001531902,0.0002476426,0.0001068977,0.000157737,0.00001241023,0.00005144639],"genre_scores_gemma":[0.9912565,0.0006616025,0.007621749,0.000001735238,0.0001704481,3.803078e-7,0.0001769812,0.000006745938,0.0001038082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01559164,"threshold_uncertainty_score":0.5418556,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2890072312","doi":"10.3390/rs10091496","title":"Detecting Building Edges from High Spatial Resolution Remote Sensing Imagery Using Richer Convolution Features Network","year":2018,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Toronto; National Natural Science Foundation of China","keywords":"Computer science; Constraint (computer-aided design); Enhanced Data Rates for GSM Evolution; Measure (data warehouse); Convolution (computer science); Edge detection; Artificial intelligence; Feature (linguistics); Building model; Aerial image; Remote sensing; Pattern recognition (psychology); Image (mathematics); Computer vision; Data mining; Image processing; Mathematics; Geology; Geometry; Simulation; Artificial neural network","retraction":null,"screen_n_in":null,"score":{"opus":0.02057838936552527,"gpt":0.2341030529680952,"spread":0.2135246636025699,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0009068601,0.0004670856,0.000522716,0.0002121526,0.001513576,0.0003668592,0.0001449097,0.0003766869,0.00005436089],"category_scores_gemma":[0.0004310144,0.0004393014,0.0001722734,0.0006204912,0.0002770733,0.0003151715,0.0000523659,0.0006189649,0.00008510464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008317391,"about_ca_system_score_gemma":0.0001080644,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1387902,"about_ca_topic_score_gemma":0.01358043,"domain_scores_codex":[0.9963632,0.0005504275,0.0005768331,0.0008697064,0.0005329059,0.001106896],"domain_scores_gemma":[0.998137,0.0004947307,0.0003130651,0.0005495971,0.0002605709,0.0002450306],"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":[0.0001849471,0.000001964307,0.0004346526,0.00001383314,0.00005830648,0.0001082028,0.0003143357,0.01671502,0.02139287,7.174019e-7,0.0002124273,0.9605627],"study_design_scores_gemma":[0.0004220568,0.00007585101,0.02231042,0.0005909535,0.0001185757,0.0003309629,0.0001317149,0.964565,0.008322701,0.001845037,0.0007055796,0.000581148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7075897,0.0006289187,0.2874063,0.0001253794,0.002791923,0.0001532867,0.000008846956,0.0002549069,0.001040713],"genre_scores_gemma":[0.7192689,0.00004023647,0.2744271,0.0002541689,0.005873684,1.674735e-10,0.00005638094,0.00002961649,0.00004991185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9599816,"threshold_uncertainty_score":0.9998059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021874608","doi":"10.1016/j.jenvman.2006.04.024","title":"Observation and simulation of net primary productivity in Qilian Mountain, western China","year":2006,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"University of Toronto; National Natural Science Foundation of China","keywords":"Primary production; China; Productivity; Net (polyhedron); Environmental science; Primary productivity; Physical geography; Geography; Ecosystem; Ecology; Biology; Mathematics; Economics; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.006478483750595628,"gpt":0.1788992426199695,"spread":0.1724207588693738,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002349235,0.00005886029,0.0001081034,0.00007402465,0.00002201543,0.00001280205,0.00004034336,0.00001801567,0.00002552733],"category_scores_gemma":[0.000001931352,0.00004688411,0.00002058237,0.00004605417,0.00002804085,0.0002059244,0.000008387585,0.00005665684,0.000001670958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001449338,"about_ca_system_score_gemma":0.000002102958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002457687,"about_ca_topic_score_gemma":0.0001709737,"domain_scores_codex":[0.999384,0.00003692539,0.0002379312,0.00008078915,0.0001845555,0.00007574734],"domain_scores_gemma":[0.9997278,0.00001516907,0.000173804,0.00006052555,0.000002129193,0.00002056431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004653322,0.00004993666,0.739355,0.00002277659,0.000007006302,0.00001282253,0.00005007298,0.1893632,0.0001447351,0.000001170542,0.00001187536,0.0709349],"study_design_scores_gemma":[0.0003415238,0.00009632463,0.9900241,0.00002488128,0.00001328218,0.00000692376,0.00004259798,0.008339318,0.00003479311,0.0002146559,0.0008138848,0.00004774351],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985459,0.0002213973,0.0001149256,0.0001159937,0.00005967053,0.00008927137,0.000003769398,0.000001583211,0.000847488],"genre_scores_gemma":[0.9989365,0.0001057011,0.0006450101,0.00002690951,0.00005308698,2.123037e-8,0.00001430613,0.000001625642,0.000216815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2506691,"threshold_uncertainty_score":0.1911879,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2110639104","doi":"10.1016/j.enggeo.2004.06.004","title":"A review of landslide problems and mitigation measures in Chongqing and Hong Kong:","year":2004,"lang":"en","type":"review","venue":"Engineering Geology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":47,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Landslide; Rockfall; Natural hazard; Flooding (psychology); Environmental planning; Geography; Civil engineering; Forensic engineering; Geology; Engineering; Geotechnical engineering; Meteorology","retraction":null,"screen_n_in":null,"score":{"opus":0.01720008942819837,"gpt":0.2244850562230197,"spread":0.2072849667948214,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003237588,0.0001726564,0.0007623261,0.0001573136,0.00001620429,0.000009522106,0.0000558878,0.0001392505,0.00001341372],"category_scores_gemma":[0.0001308618,0.0001311283,0.00004889986,0.000160357,0.00003233257,0.00003807165,0.000008713479,0.0002155731,0.000002765134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004351439,"about_ca_system_score_gemma":0.00004134774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006283861,"about_ca_topic_score_gemma":0.0003279598,"domain_scores_codex":[0.9991739,0.00005602238,0.000327216,0.0002023137,0.00006499424,0.0001755228],"domain_scores_gemma":[0.9996026,0.0001303758,0.0001033425,0.00009908431,0.00001286246,0.00005178795],"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":[5.498426e-7,0.000001813252,0.001454889,0.0908021,0.00001964572,0.00001099203,0.00005291827,0.0009942058,1.652313e-7,0.000006156289,0.000006192541,0.9066504],"study_design_scores_gemma":[0.0002692227,0.00006863141,0.006956216,0.2876775,0.0001717167,0.0004774531,0.000005932533,0.00134448,4.288079e-7,0.00005066684,0.7025639,0.0004138321],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006381315,0.9988368,0.00005174402,0.00002400507,0.000108407,0.0002131587,0.000005179035,0.00001863216,0.0001039495],"genre_scores_gemma":[0.0005983044,0.9986849,0.000581087,0.00001493463,0.00003673357,5.770997e-7,0.00006546222,0.000005663838,0.00001226515],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9062365,"threshold_uncertainty_score":0.5347255,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2301398174","doi":"10.1080/07038992.2015.1065705","title":"Biparabolic NDVI-T<sub>s</sub> Space and Soil Moisture Remote Sensing in an Arid and Semi arid Area","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Normalized Difference Vegetation Index; Moderate-resolution imaging spectroradiometer; Arid; Environmental science; Vegetation (pathology); Remote sensing; Water content; Geography; Satellite; Geology; Physics; Climate change","retraction":null,"screen_n_in":null,"score":{"opus":0.02043048623363228,"gpt":0.2083195211795401,"spread":0.1878890349459079,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009793116,0.0003090648,0.0005281859,0.0006088346,0.0002615681,0.0003549333,0.0001093527,0.0002220303,0.000002904739],"category_scores_gemma":[0.0002866079,0.0002723522,0.00006472866,0.0003871887,0.0002166968,0.00036351,0.000008966325,0.0007077463,0.000005498618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000559049,"about_ca_system_score_gemma":0.0008593866,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1165133,"about_ca_topic_score_gemma":0.633351,"domain_scores_codex":[0.9979265,0.0002428825,0.0004860251,0.0003519234,0.0003124107,0.000680269],"domain_scores_gemma":[0.9972603,0.0001090263,0.0002883226,0.0002604883,0.0002361893,0.001845626],"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":[0.00007349337,0.000001524277,0.009165211,0.00001816327,0.00002393269,0.002664174,0.002389544,0.002391589,0.0011142,9.865171e-7,0.0004469086,0.9817103],"study_design_scores_gemma":[0.00250673,0.0005769322,0.1412449,0.001431604,0.0001522541,0.02600105,0.003887427,0.799726,0.004220484,0.003514895,0.01545909,0.001278615],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929331,0.002405343,0.001191837,0.00127465,0.0007141836,0.00009112647,0.00001123472,0.00001596662,0.001362583],"genre_scores_gemma":[0.9826782,0.0003345209,0.01592317,0.0005284186,0.0004777283,1.849579e-10,0.00001338208,0.00001868342,0.00002592548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9804317,"threshold_uncertainty_score":0.9999729,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2003009239","doi":"10.1016/s0305-9006(03)00062-x","title":"Remote sensing for mapping and monitoring land-cover and land-use change","year":2003,"lang":"en","type":"article","venue":"Progress in Planning","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":35,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Land cover; Remote sensing; Cover (algebra); Change detection; Land use; Environmental resource management; Land use, land-use change and forestry; Geography; Environmental science; Engineering; Civil engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.07275574569961979,"gpt":0.2805068656247641,"spread":0.2077511199251443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003347285,0.0001258516,0.0001651057,0.0001063034,0.0001552143,0.0001671066,0.00003103375,0.00007153318,0.00000347692],"category_scores_gemma":[0.00007670826,0.0001050326,0.00001646804,0.00009977088,0.00004067807,0.0002113803,0.000007330416,0.000122971,0.00000215998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003003937,"about_ca_system_score_gemma":0.000007646354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004779416,"about_ca_topic_score_gemma":0.00005716038,"domain_scores_codex":[0.9991505,0.00005119964,0.0001417428,0.0002466446,0.00009561868,0.0003142904],"domain_scores_gemma":[0.9995447,0.0002257558,0.00005196818,0.00008194808,0.00001629616,0.00007928388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001987777,0.000001140062,0.7439858,0.0000348393,0.000005267865,0.00003278886,0.0007491875,0.000061007,0.00000164021,9.242531e-7,0.000004825715,0.2551027],"study_design_scores_gemma":[0.0006347249,0.00004969335,0.9003965,0.0004988066,0.00001024553,0.0001110768,0.0001532826,0.09069636,0.00005749582,0.0001792963,0.006984027,0.0002285423],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923802,0.006353091,0.0003124613,0.00005365011,0.0002762028,0.0001975294,0.000007409695,0.00003973826,0.0003796879],"genre_scores_gemma":[0.9746855,0.0001734736,0.02487371,0.00004881932,0.0001599897,1.353746e-7,0.00001324379,0.000006447432,0.0000386355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2548742,"threshold_uncertainty_score":0.4283104,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2474445233","doi":"10.3390/rs8070568","title":"Estimation of Continuous Urban Sky View Factor from Landsat Data Using Shadow Detection","year":2016,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Simon Fraser University; University of Ottawa","funders":"Simon Fraser University","keywords":"Environmental science; Lidar; Remote sensing; Pixel; Meteorology; Geography; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.04269952114548452,"gpt":0.2485186891208417,"spread":0.2058191679753572,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001872341,0.0001448825,0.000259518,0.00007599749,0.0001129731,0.00004882034,0.0001301218,0.00009453097,0.00007123992],"category_scores_gemma":[0.0001751256,0.00009436814,0.00004513171,0.0001350335,0.0000507226,0.0002718924,0.00002036284,0.00007991526,0.0000477113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009613983,"about_ca_system_score_gemma":0.00003337717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293575,"about_ca_topic_score_gemma":0.002468986,"domain_scores_codex":[0.9988203,0.0001136538,0.000282092,0.0003335395,0.0002220231,0.0002283711],"domain_scores_gemma":[0.9989414,0.0002394436,0.0001800693,0.0005100851,0.00004429518,0.00008467556],"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":[0.00002738757,0.000001879379,0.001558234,0.000009931357,0.00001748639,0.000009060361,0.00009112346,0.0003910974,0.01087516,1.21116e-7,0.00001872631,0.9869998],"study_design_scores_gemma":[0.0003286332,0.00003573783,0.01578628,0.0003359119,0.00004118862,0.00004199774,0.00002819588,0.9754525,0.006602874,0.0001788096,0.000994238,0.0001736642],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9254106,0.0003194622,0.07302771,0.00006353486,0.0004462507,0.00009133458,0.0001381381,0.00006155648,0.0004414673],"genre_scores_gemma":[0.9832919,0.00007443706,0.01621658,0.00003832909,0.0002221937,1.293288e-10,0.0001122506,0.000007490601,0.00003679927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9868261,"threshold_uncertainty_score":0.9936372,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393041651","doi":"10.1080/10095020.2024.2311862","title":"Ecological health assessment of Tibetan alpine grasslands in Gannan using remote sensed ecological indicators","year":2024,"lang":"en","type":"article","venue":"Geo-spatial Information Science","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Ecology; Ecological assessment; Geography; Ecological health; Ecological indicator; Environmental science; Biology; Ecosystem","retraction":null,"screen_n_in":null,"score":{"opus":0.02370184339988522,"gpt":0.3103474485591825,"spread":0.2866456051592973,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002195125,0.0001276499,0.00024313,0.0006982604,0.0002304202,0.0001994032,0.000230482,0.00008838211,0.0002544952],"category_scores_gemma":[0.0001437167,0.00008803479,0.0000490721,0.001612389,0.0002841316,0.001003777,0.00002951803,0.0002442708,0.00003290669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005513126,"about_ca_system_score_gemma":0.0007601387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006357778,"about_ca_topic_score_gemma":0.002518579,"domain_scores_codex":[0.9980116,0.0001015857,0.000621353,0.0002219512,0.0006107698,0.0004326811],"domain_scores_gemma":[0.9992763,0.0001218301,0.0001964127,0.0001607812,0.00006247639,0.0001821541],"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":[0.00002818584,0.00004559736,0.1406277,0.0001089752,0.000009504163,0.00002471023,0.00173175,0.06050784,0.000152605,0.0001926332,0.0001605474,0.7964099],"study_design_scores_gemma":[0.00009835327,0.0001515471,0.478938,0.00003039025,0.000001694694,0.00001390425,0.0000785159,0.5196283,0.00004774304,0.00006722056,0.0008766831,0.00006762573],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826218,0.00003523752,0.01110165,0.0006181014,0.0006107886,0.0002136319,0.00003361485,0.00005280695,0.004712297],"genre_scores_gemma":[0.9958723,0.00005050526,0.003603384,0.0003564481,0.00004111701,9.260757e-8,0.00006617759,0.000001345256,0.000008671604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7963423,"threshold_uncertainty_score":0.9611101,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2981642257","doi":"10.4095/219795","title":"Estimation of Crop Cover and Chlorophyll from Hyperspectral Remote Sensing","year":2001,"lang":"en","type":"report","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":26,"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":"Hyperspectral imaging; Remote sensing; Cover (algebra); Estimation; Crop; Environmental science; Chlorophyll; Cover crop; Geography; Biology; Agroforestry; Forestry; Botany; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02468746234124715,"gpt":0.2430002067319242,"spread":0.218312744390677,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002165699,0.0002136421,0.0004179667,0.0001009563,0.00007252993,0.00006721356,0.00006110658,0.0002432951,0.001084569],"category_scores_gemma":[0.0001073132,0.0001586283,0.00008159952,0.0001070047,0.00008204648,0.00007288476,0.000007381132,0.0002161526,0.00008883972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000966524,"about_ca_system_score_gemma":0.000197687,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1466421,"about_ca_topic_score_gemma":0.002514903,"domain_scores_codex":[0.998601,0.00004117711,0.0003216022,0.0003394583,0.0004857256,0.0002110484],"domain_scores_gemma":[0.99922,0.0001278903,0.0002092036,0.0002460246,0.00009650734,0.0001003371],"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":[0.00003177983,0.000002738906,0.001252421,0.00004018611,0.00004797462,0.00007788914,0.00008616211,0.00261042,0.00002110732,2.867632e-7,0.00201262,0.9938164],"study_design_scores_gemma":[0.0004340155,0.0001648859,0.09061637,0.0004050573,0.0002183437,0.0004934677,0.00007657304,0.8644056,0.0003817293,0.000889159,0.04128433,0.0006305114],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6715288,0.001607554,0.002100541,0.00007182393,0.0008417398,0.0001197644,0.0001203819,0.00005685728,0.3235526],"genre_scores_gemma":[0.9388553,0.005305666,0.03909997,0.0000922993,0.0007713881,1.961665e-9,0.001024241,0.00001623631,0.01483489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9931859,"threshold_uncertainty_score":0.9998286,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2570238107","doi":"10.1111/1755-0998.12653","title":"Spatial detection of outlier loci with Moran eigenvector maps","year":2017,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Ciencia y Tecnología; Duke University","keywords":"Biology; Anomaly detection; Outlier; Cartography; Spatial analysis; Eigenvalues and eigenvectors; Computational biology; Evolutionary biology; Pattern recognition (psychology); Statistics; Artificial intelligence; Computer science; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.006643532203069538,"gpt":0.189537363418695,"spread":0.1828938312156254,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000127445,0.0001037382,0.0001796376,0.00005749652,0.0003010521,0.00005082499,0.0001981732,0.00009822257,0.0001591053],"category_scores_gemma":[0.00004915525,0.00007418305,0.00004777557,0.00003257642,0.0002228185,0.00004542771,0.00001153526,0.0001040877,0.00004754295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002106979,"about_ca_system_score_gemma":0.00001633776,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005357671,"about_ca_topic_score_gemma":0.02656312,"domain_scores_codex":[0.9992594,0.00008051872,0.0001224007,0.0002009453,0.0001316444,0.0002051602],"domain_scores_gemma":[0.999375,0.0000287074,0.0001560508,0.0003393768,0.00003287058,0.00006800904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002126963,0.00001774326,0.9218804,0.00001491833,0.00007284295,0.0001572275,0.0003173881,0.001115118,0.002885207,0.000002267921,0.0000312795,0.07329294],"study_design_scores_gemma":[0.0004035105,0.000412316,0.9826913,0.000007100489,0.00003312117,0.00003477154,0.00005070813,0.002361696,0.009354996,0.00008509773,0.004445501,0.0001198674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929651,0.00009910863,0.0003374552,0.0001476187,0.0001438317,0.00009064889,0.00001160307,0.00002115184,0.006183499],"genre_scores_gemma":[0.9994322,0.000006893549,0.0002117058,0.0000799279,0.00006360222,1.711695e-7,0.00001649171,0.000004668153,0.0001843182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07317307,"threshold_uncertainty_score":0.9911996,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2907471899","doi":"10.2495/dne-v13-n4-384-394","title":"Effects of vertical green technology on building surface temperature","year":2018,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Ministero dello Sviluppo Economico","keywords":"Architectural engineering; Engineering; Environmental science; Engineering physics","retraction":null,"screen_n_in":null,"score":{"opus":0.005478455810055019,"gpt":0.2282371526092566,"spread":0.2227586967992016,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020561,0.00008935911,0.0001575956,0.0001902662,0.00004339618,0.00003152543,0.0002152213,0.0002211089,0.00001576716],"category_scores_gemma":[0.000147368,0.00006155799,0.00004652422,0.000123582,0.00008944081,0.00009495775,0.000009031291,0.0004406108,0.000003797785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007045364,"about_ca_system_score_gemma":0.00003805141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002964614,"about_ca_topic_score_gemma":0.00004514391,"domain_scores_codex":[0.9992791,0.00004409484,0.0002038464,0.00009882776,0.0002611821,0.0001129944],"domain_scores_gemma":[0.9992557,0.000273452,0.0001042943,0.00005570089,0.0002528223,0.00005803613],"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":[0.008394313,0.0005469032,0.2176277,0.0002171841,0.002393109,0.002651299,0.001513583,0.02450142,0.179022,0.00792593,0.004203745,0.5510029],"study_design_scores_gemma":[0.006472549,0.00974081,0.4311028,0.002125388,0.0003567917,0.004532295,0.0002753008,0.3247173,0.1719213,0.04054287,0.007067109,0.001145411],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961083,0.0006427253,0.001053056,0.0009123919,0.001018263,0.00004008287,0.000005663096,0.000007321283,0.0002121801],"genre_scores_gemma":[0.994219,0.0002079721,0.004997238,0.0002312842,0.0003093703,8.163509e-9,0.00000250947,0.000003041812,0.00002958512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5498574,"threshold_uncertainty_score":0.2510262,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2066626129","doi":"10.1109/igarss.2014.6946930","title":"Stereo-based building detection in very high resolution satellite imagery using IHS color system","year":2014,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":20,"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":"Artificial intelligence; Computer vision; Hue; Computer science; Brightness; Satellite; Remote sensing; Segmentation; Image segmentation; Roof; Image resolution; Object detection; Geography; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01398074120851722,"gpt":0.2025972673709231,"spread":0.1886165261624059,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005519524,0.0001064147,0.0001524309,0.0001652684,0.000133391,0.00008409443,0.00005743595,0.00008212258,0.00003184562],"category_scores_gemma":[0.00003445312,0.00008413544,0.00003780786,0.0002230548,0.0000251217,0.0001521432,0.000003568148,0.0001024824,0.00005056451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002471855,"about_ca_system_score_gemma":0.00002351246,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0142373,"about_ca_topic_score_gemma":0.005360446,"domain_scores_codex":[0.9989582,0.0001976111,0.0002139625,0.0002218531,0.0001531554,0.0002551869],"domain_scores_gemma":[0.9995388,0.0001613736,0.00006532385,0.000145351,0.0000238705,0.00006523325],"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":[0.0005251276,0.00002790032,0.1667808,0.0002520401,0.00001790173,0.00005475209,0.0001152236,0.2612179,0.01307528,0.00009957505,0.00002960486,0.5578039],"study_design_scores_gemma":[0.0002847133,0.0000612146,0.1678638,0.00008826164,0.000007863605,0.00001437717,0.0000554586,0.8276991,0.003211803,0.00002026106,0.0005730126,0.0001201855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829346,0.00007274338,0.01346238,0.00002707633,0.0005646623,0.00009309052,0.000002755967,0.00009984595,0.00274287],"genre_scores_gemma":[0.9943184,0.000005616246,0.005396612,0.00008382246,0.0001356043,6.272795e-8,0.00001471063,0.000003801807,0.0000413995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5664812,"threshold_uncertainty_score":0.992327,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2160152622","doi":"10.1080/01431160050021312","title":"Comparison of three different methods to select feature for discriminating forest cover types using SAR imagery","year":2000,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Pattern recognition (psychology); Principal component analysis; Artificial intelligence; Computer science; Feature selection; Land cover; Partition (number theory); Artificial neural network; Feature (linguistics); Data mining; Mathematics; Land use","retraction":null,"screen_n_in":null,"score":{"opus":0.0487945942552737,"gpt":0.3579496431276622,"spread":0.3091550488723885,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004284178,0.0001390438,0.0003496261,0.0001848768,0.00008271253,0.00008825692,0.000182307,0.00006193559,0.00006901249],"category_scores_gemma":[0.0002320408,0.0001006619,0.0001763925,0.0001045973,0.00003323378,0.00013891,0.000009131925,0.0001938946,0.000003639011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002247113,"about_ca_system_score_gemma":0.00004807639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004633216,"about_ca_topic_score_gemma":0.0005016204,"domain_scores_codex":[0.9987584,0.00009095116,0.0004433251,0.0001365747,0.0003782974,0.0001924107],"domain_scores_gemma":[0.998697,0.0003970451,0.0003334222,0.00008872518,0.0003867905,0.00009703561],"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":[0.0003236494,0.00001100756,0.00881222,0.00001172634,0.0001038981,0.0000178055,0.0003526621,0.05048893,0.003116992,0.000001385168,0.0002138565,0.9365458],"study_design_scores_gemma":[0.0004421266,0.0002094086,0.0310222,0.0003905444,0.00008494199,0.0003662405,0.00009353181,0.9539835,0.008444071,0.0008140294,0.003985281,0.0001640625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7876973,0.0002193479,0.2102369,0.0004212741,0.0007466613,0.00007445343,0.00001282201,0.000006660887,0.0005845896],"genre_scores_gemma":[0.6352851,0.00001246665,0.364166,0.00008803435,0.0003624833,5.326418e-10,0.000009046432,0.000005667838,0.00007114788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9363818,"threshold_uncertainty_score":0.4104874,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2377074150","doi":"","title":"The comparison of spatial characteristics in urban landuse growth among the central and sub-cities in Shanghai Region","year":2003,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"CAE (Canada)","funders":"","keywords":"Urbanization; Geography; Land use; Spatial ecology; Spatial variability; Scale (ratio); Spatial distribution; Common spatial pattern; Physical geography; Spatial heterogeneity; Urban planning; Cartography; Economic geography; Remote sensing; Ecology; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.01460497606773815,"gpt":0.1983804976833308,"spread":0.1837755216155927,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002133262,0.00006420479,0.0001196776,0.00003019967,0.00007829765,0.00004709816,0.00006502655,0.00003844767,0.00001017596],"category_scores_gemma":[0.0000719401,0.00003105866,0.0000144865,0.00007970115,0.0001013541,0.00004738852,0.000003375428,0.0001101182,0.000001076062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001952842,"about_ca_system_score_gemma":0.00001509269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02051716,"about_ca_topic_score_gemma":0.1137821,"domain_scores_codex":[0.999327,0.0001335772,0.0001810285,0.00008581749,0.00009228104,0.0001803036],"domain_scores_gemma":[0.9996061,0.0002099747,0.00005605757,0.00008524683,0.00001074854,0.00003185173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002665253,0.00000630022,0.9930581,0.000004776241,0.000001875821,0.000003998455,0.001033661,0.00001947914,0.000001518791,0.0001229174,0.0001293567,0.005591299],"study_design_scores_gemma":[0.0001689234,0.00003275807,0.9856941,0.00001945732,0.000002635426,0.000003451137,0.0005946386,0.01291673,0.000100896,0.0001165076,0.0003003113,0.00004958741],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970482,0.0002519348,0.00002191338,0.0001634261,0.0001275943,0.00007552144,0.000002611318,0.000005474483,0.002303308],"genre_scores_gemma":[0.9995893,0.0002289434,0.000009703786,0.00003279944,0.0000305682,5.547856e-8,0.000007823863,0.000001346986,0.00009948533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09326492,"threshold_uncertainty_score":0.9860053,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200542190","doi":"10.1155/2021/4310321","title":"Recognition of Ziziphus lotus through Aerial Imaging and Deep Transfer Learning Approach","year":2021,"lang":"en","type":"article","venue":"Mobile Information Systems","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":true,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Taif University","keywords":"Computer science; Transfer of learning; Artificial intelligence; Lotus; Convolutional neural network; Rhamnaceae; Ziziphus; Deep learning; Robinia; Machine learning; Pattern recognition (psychology); Ecology; Botany","retraction":{"nature":"Retraction","openalex_flagged":true},"screen_n_in":null,"score":{"opus":0.01317921993748305,"gpt":0.1953561059763262,"spread":0.1821768860388432,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002102827,0.00007567693,0.0001462479,0.00004326483,0.00009901988,0.0001285146,0.00003087564,0.00004588572,0.00006109347],"category_scores_gemma":[0.0000218588,0.00006292164,0.00003057141,0.0001262314,0.00002724415,0.000767855,0.000003040886,0.00008439588,0.00004185826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002790718,"about_ca_system_score_gemma":0.000023714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019954,"about_ca_topic_score_gemma":0.00002992565,"domain_scores_codex":[0.9992244,0.00008997366,0.0003146083,0.00008282899,0.0001648409,0.0001233038],"domain_scores_gemma":[0.9996774,0.00004284945,0.00006792119,0.00007404728,0.00009994232,0.00003787959],"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":[0.00008462336,0.00001833484,0.0220201,0.0005954443,0.00003946895,0.000006427402,0.01548524,0.1915649,0.0001438785,0.00003982196,0.0001105186,0.7698912],"study_design_scores_gemma":[0.001957766,0.0001751878,0.0225992,0.0002276368,0.00005476458,0.000685724,0.0292575,0.8404775,0.001236236,0.00006350099,0.1027603,0.0005046625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9374827,0.001119348,0.01281375,0.000009782489,0.0005999774,0.0002347321,0.00003444493,0.00005584879,0.04764946],"genre_scores_gemma":[0.9987778,0.0001526883,0.0003919177,0.00003176731,0.00008486522,9.587433e-7,0.0005255174,0.000001771705,0.00003269943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7693865,"threshold_uncertainty_score":0.256587,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4250908727","doi":"10.5194/isprsarchives-xli-b8-1371-2016","title":"TOWARDS CONSISTENT MAPPING OF URBAN STRUCTURES – GLOBAL HUMAN SETTLEMENT LAYER AND LOCAL CLIMATE ZONES","year":2016,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; University of Victoria","funders":"","keywords":"Comparability; Geography; Grid; Scale (ratio); Population; Thematic map; Urban planning; Cartography; Computer science; Mathematics; Civil engineering; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02053221677100472,"gpt":0.2512015612130637,"spread":0.230669344442059,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001226107,0.0003837781,0.0004473125,0.0005489992,0.00114569,0.0004619871,0.001024113,0.00008810755,0.00001840687],"category_scores_gemma":[0.0003486439,0.0002034221,0.0002909259,0.0005942983,0.003860365,0.0003854457,0.0004949409,0.0002417727,0.000002129543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002403277,"about_ca_system_score_gemma":0.0001717375,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7745481,"about_ca_topic_score_gemma":0.2794244,"domain_scores_codex":[0.9959074,0.0002904948,0.001340987,0.0003833017,0.001561598,0.0005162199],"domain_scores_gemma":[0.9970825,0.0006966204,0.001425989,0.0003796562,0.0002415487,0.0001736403],"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":[0.0001363227,0.000009931852,0.004317059,0.00004973102,0.00009023579,4.139487e-7,0.001745145,0.001184122,0.0009458474,0.00002183672,0.00003360631,0.9914657],"study_design_scores_gemma":[0.000785564,0.0001706075,0.05989249,0.0004101288,0.0000428226,0.0001476826,0.001938927,0.923564,0.003158629,0.007368011,0.002257707,0.0002634317],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08528847,0.00006716818,0.8991765,0.003571,0.00143623,0.0005021526,0.0004447175,0.00003741242,0.009476291],"genre_scores_gemma":[0.9961925,0.0002432735,0.002731181,0.0006378687,0.0001119811,6.254636e-8,0.00004397666,0.000005424994,0.00003378917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9912023,"threshold_uncertainty_score":0.9988506,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2148955138","doi":"10.1109/igarss.1996.516452","title":"SAR image segmentation by mathematical morphology and texture analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Université de Sherbrooke","keywords":"Synthetic aperture radar; Artificial intelligence; Image segmentation; Mathematical morphology; Computer science; Context (archaeology); Image texture; Segmentation; Land cover; Computer vision; Remote sensing; Radar imaging; Pixel; Enhanced Data Rates for GSM Evolution; Pattern recognition (psychology); Texture (cosmology); Image (mathematics); Geography; Image processing; Land use; Radar; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.009884680888444705,"gpt":0.2060170732277097,"spread":0.196132392339265,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006055849,0.00005568924,0.0001023891,0.00004747529,0.00005418649,0.00004022137,0.00002888578,0.00003854326,0.0128267],"category_scores_gemma":[0.000009294332,0.000035947,0.00002772801,0.0001493314,0.0000386425,0.00006222592,0.000001970499,0.0000437993,0.0003288931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":6.187835e-7,"about_ca_system_score_gemma":8.061274e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003392148,"about_ca_topic_score_gemma":0.0001501473,"domain_scores_codex":[0.999584,0.00002976277,0.00008318192,0.0001222695,0.0000747693,0.0001060618],"domain_scores_gemma":[0.9997898,0.00005111283,0.00001847997,0.00007308732,0.000007399284,0.00006013493],"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":[0.00002418269,0.00008868777,0.3228981,0.00003542516,0.0004786889,0.00008759018,0.001563746,0.0004544243,0.002700377,0.00008167394,0.1129758,0.5586112],"study_design_scores_gemma":[0.0004366316,0.0001170681,0.1422026,0.000003634261,0.0003351856,0.00009802459,0.0004140151,0.8509174,0.0005173826,0.0008663079,0.003820761,0.0002710244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.949112,0.0002945918,0.004643267,0.0006432799,0.00002467077,0.00004425918,0.0000206705,0.00003403917,0.04518324],"genre_scores_gemma":[0.9897988,0.00009148144,0.006673608,0.0003361055,0.0000171452,1.269868e-8,0.00007260469,0.0000010443,0.003009175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.850463,"threshold_uncertainty_score":0.9880757,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2152261845","doi":"10.1109/igarss.2006.589","title":"A Global Crop Growth Monitoring System Based on Remote Sensing","year":2006,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Crop; Agriculture; Growing season; Crop yield; Agricultural engineering; Environmental science; Geography; Agronomy; Engineering; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01000658294746567,"gpt":0.1991554621511918,"spread":0.1891488792037261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001477871,0.0001296796,0.0001309075,0.0000455015,0.0001720927,0.000110945,0.00006739727,0.00006148059,0.00003419479],"category_scores_gemma":[0.00001402116,0.00009290179,0.00005674069,0.0002155738,0.00002066595,0.0000483541,0.00000250253,0.00006446576,0.000185759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001572326,"about_ca_system_score_gemma":0.0000262129,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04977619,"about_ca_topic_score_gemma":0.001797269,"domain_scores_codex":[0.9990168,0.00006173101,0.0001555444,0.0002303948,0.0002539254,0.000281561],"domain_scores_gemma":[0.999606,0.00006362424,0.00003991946,0.0001713378,0.00003635562,0.00008276269],"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":[0.0001797007,0.00001588557,0.4248569,0.00009911657,0.00001674472,0.0005380627,0.00002373482,0.1063411,0.00004218271,0.0001803824,0.002128335,0.4655779],"study_design_scores_gemma":[0.0002386425,0.00005250818,0.272393,0.0001018258,0.000008501095,0.00004221089,0.00004098456,0.7261488,0.0002066344,0.0001192786,0.0004982712,0.0001493493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6795442,0.0000431075,0.00657922,0.0001407971,0.0007607429,0.00006943887,0.0000107442,0.0002712427,0.3125805],"genre_scores_gemma":[0.9879465,0.000001251091,0.01118013,0.00008232619,0.0004596169,1.489029e-9,0.00001671833,0.00000291032,0.0003106126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6198077,"threshold_uncertainty_score":0.9565514,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2797741687","doi":"","title":"The revised Davenport roughness classification for cities and sheltered country","year":2000,"lang":"en","type":"article","venue":"Davis Meeting","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02013326227721248,"gpt":0.2291236476592225,"spread":0.20899038538201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004665032,0.00007215948,0.00008619556,0.00001231146,0.0005063093,0.0001666208,0.00007439239,0.00003515542,0.00007039718],"category_scores_gemma":[0.00006284534,0.00004539727,0.00002205886,0.00005946903,0.00005746948,0.00007771917,0.000001965297,0.00005167162,0.00001396217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001783948,"about_ca_system_score_gemma":0.00001472692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004421563,"about_ca_topic_score_gemma":0.0003505439,"domain_scores_codex":[0.9993732,0.00004458148,0.0001533936,0.0001492502,0.0001032247,0.0001763591],"domain_scores_gemma":[0.9994844,0.0002735768,0.00005133612,0.000127159,0.00002291199,0.00004068497],"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":[0.00007922157,0.000002962103,0.05446317,0.00003110632,0.000010734,0.000001748482,0.0004139685,0.0002291768,0.00004432458,0.0000513076,0.001594102,0.9430782],"study_design_scores_gemma":[0.0003884643,0.00005506802,0.4270231,0.00009971762,0.00002655731,0.00002005135,0.0007973626,0.1493512,0.00005423052,0.0004606871,0.4215228,0.000200735],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714044,0.0008582945,0.00002451254,0.0004273744,0.0001624476,0.0001578008,0.0000345407,0.00003929182,0.0268913],"genre_scores_gemma":[0.9971377,0.0005943247,0.0004134536,0.0001596982,0.0001985546,4.851174e-7,0.0001501901,0.000003485778,0.001342131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9428774,"threshold_uncertainty_score":0.3894173,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2982053709","doi":"10.4095/219855","title":"Application of Hyperspectral Remote Sensing for LAI Estimation in Precision Farming","year":2001,"lang":"en","type":"report","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":15,"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":"Hyperspectral imaging; Remote sensing; Precision agriculture; Estimation; Environmental science; Agriculture; Computer science; Geography; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03153163607116227,"gpt":0.2874242434313272,"spread":0.2558926073601649,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000733508,0.0001598782,0.0003365995,0.0002267801,0.00005404644,0.00002730137,0.00007749855,0.0002336009,0.00003588436],"category_scores_gemma":[0.0002239063,0.0001283803,0.00009444417,0.0002124654,0.00002218587,0.00006628145,0.000003944296,0.0001530285,0.00001037083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002510836,"about_ca_system_score_gemma":0.0001779373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03923417,"about_ca_topic_score_gemma":0.01211091,"domain_scores_codex":[0.9986069,0.00003467462,0.0004457361,0.0003187015,0.0003784585,0.000215485],"domain_scores_gemma":[0.9990836,0.0002277912,0.0002625932,0.0002245172,0.0001551438,0.00004632562],"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":[0.00003100157,0.000003740418,0.001456813,0.00007624504,0.000007085579,0.000003258015,0.00005679234,0.006886281,0.0000263971,0.000001200565,0.0002914499,0.9911597],"study_design_scores_gemma":[0.0002051433,0.00006218263,0.01439905,0.0002120072,0.0000293775,0.00008046654,0.00005454377,0.9672993,0.0001578556,0.0009308415,0.01638401,0.000185211],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1569469,0.001157922,0.5760952,0.0002008966,0.001035502,0.00174639,0.00007138545,0.0001425213,0.2626033],"genre_scores_gemma":[0.7134475,0.00143055,0.2787801,0.00004093432,0.000480715,8.477927e-8,0.001727403,0.00002200165,0.004070673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9909745,"threshold_uncertainty_score":0.9671637,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2901370348","doi":"10.1201/9781003541172-10","title":"Ecological Characterization of Vegetation Using Multi-Sensor Remote Sensing in the Solar Reflective Spectrum","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Remote sensing; Characterization (materials science); Vegetation (pathology); Spectrum (functional analysis); Environmental science; Geography; Ecology; Materials science; Nanotechnology; Biology; Physics; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.04397722427737351,"gpt":0.2555518237693888,"spread":0.2115745994920153,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003334678,0.0002059364,0.0002804401,0.0001926677,0.00007582961,0.0000656092,0.00008390596,0.0002562565,0.0001550341],"category_scores_gemma":[0.00002190707,0.0001250434,0.00009678754,0.00008407387,0.00006513778,0.00006495464,0.000007461171,0.0003902918,0.00008619423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001428784,"about_ca_system_score_gemma":0.00004417062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009830794,"about_ca_topic_score_gemma":0.003820763,"domain_scores_codex":[0.9988905,0.00007262373,0.0003342036,0.0003102946,0.0002095302,0.0001828547],"domain_scores_gemma":[0.9994735,0.0001283804,0.0001630729,0.0001686954,0.00003585395,0.00003050604],"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":[0.0005594512,0.00008283572,0.002123468,0.0009941855,0.0005159966,0.002211858,0.009783858,0.00785917,0.01764247,0.004277234,0.00004637217,0.9539031],"study_design_scores_gemma":[0.0002796091,0.0002001251,0.04471411,0.000595911,0.0001341363,0.0001950397,0.00009947918,0.9372178,0.0003901181,0.01222062,0.003492984,0.0004601077],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3477667,0.0003916664,0.008442676,0.0006807093,0.001538801,0.0009791659,0.00007738864,0.0001326006,0.6399903],"genre_scores_gemma":[0.9217525,0.0004016133,0.01520149,0.0005003079,0.0005493163,1.11703e-8,0.0006338437,0.0000309669,0.06092991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.953443,"threshold_uncertainty_score":0.509912,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2981672736","doi":"10.4095/225402","title":"Fourth generation seismic hazard maps of Canada: Maps and grid values to be used with the 2005 National Building Code of Canada","year":2008,"lang":"en","type":"report","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":14,"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":"Seismic hazard; Grid; Code (set theory); Hazard; Geography; Building code; Hazard map; Computer science; Seismology; Cartography; Environmental resource management; Environmental science; Geology; Civil engineering; Engineering; Geodesy; Programming language; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.03264355663722579,"gpt":0.2184480590983446,"spread":0.1858045024611188,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004671876,0.000190755,0.0003365453,0.00007740729,0.0002077224,0.00002337043,0.0001240418,0.00007830419,0.0000723737],"category_scores_gemma":[0.00007437546,0.0001109344,0.00002861741,0.0001190049,0.00005553491,0.00004146103,0.000008359322,0.0001466712,1.497234e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000697008,"about_ca_system_score_gemma":0.01347983,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957352,"about_ca_topic_score_gemma":0.9999028,"domain_scores_codex":[0.9976254,0.00006161206,0.00031362,0.0002537772,0.001487441,0.0002581571],"domain_scores_gemma":[0.9989699,0.0001503604,0.000237292,0.0001599328,0.0003398975,0.0001426214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001791928,0.000002770385,0.006205007,0.00004231223,0.0000817906,0.00002449471,0.00008192021,0.08259724,0.00001297332,0.000003782349,0.9096018,0.001328001],"study_design_scores_gemma":[0.0002809601,0.0001103536,0.03985476,0.000111682,0.00006736794,0.000370274,0.0001819032,0.04051239,0.0005820009,0.00001683773,0.9174925,0.0004189659],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372048,0.001453558,0.0003225702,0.009353616,0.0017575,0.0006177853,0.006133502,0.0000229002,0.04313376],"genre_scores_gemma":[0.9645979,0.001111534,0.00411663,0.001959486,0.001377069,5.842467e-7,0.002778673,0.0000226975,0.02403538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04208485,"threshold_uncertainty_score":0.9921128,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2997247601","doi":"10.18280/isi.240611","title":"Classification of Urban Land Use Based on Graph Theory and Geographic Information System","year":2019,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Geographic information system; Computer science; Land use; Geography; Graph theory; Graph; Theoretical computer science; Cartography; Mathematics; Engineering; Civil engineering; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.009665912447099925,"gpt":0.1824021620443239,"spread":0.1727362495972239,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006526053,0.0001233029,0.0001617939,0.000418906,0.0001222391,0.0002014044,0.0000755784,0.00009943212,0.00003323802],"category_scores_gemma":[0.0001047522,0.00009527919,0.0000468593,0.0002812683,0.00007687489,0.002536055,0.000004148754,0.00008701815,0.0001055327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000115789,"about_ca_system_score_gemma":0.0000307155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005808302,"about_ca_topic_score_gemma":0.00003194685,"domain_scores_codex":[0.9989787,0.000122498,0.0004166117,0.00007856108,0.0002477082,0.0001558668],"domain_scores_gemma":[0.999077,0.000205493,0.0003156245,0.0002116039,0.0001281718,0.00006216436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002731232,0.000004570833,0.9287553,0.0005059718,0.00001618986,2.616815e-7,0.001429806,0.005866736,0.000007793646,0.002145587,0.00004606428,0.06094859],"study_design_scores_gemma":[0.0003858477,0.0001442902,0.8428922,0.0001981566,0.00001275901,0.000007390027,0.0007778713,0.154522,0.00002823539,0.0001754796,0.0007398863,0.000115837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985907,0.00002962621,0.002201459,0.0000103115,0.0002277692,0.000280968,0.00007032794,0.00008027112,0.01119229],"genre_scores_gemma":[0.9991517,0.00001391777,0.0002418553,0.0001117497,0.00001533874,6.142644e-7,0.0004519659,0.000002086601,0.00001077358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1486553,"threshold_uncertainty_score":0.3885373,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4292023938","doi":"10.1016/j.jhydro1.2005.02.042","title":"Multifractals, cloud radiances and rain","year":2006,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Cloud computing; Environmental science; Remote sensing; Meteorology; Geography; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01391405847055743,"gpt":0.2022776154941129,"spread":0.1883635570235555,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005277595,0.0004961441,0.0005498094,0.0001607141,0.0007431611,0.0008030272,0.0007455548,0.0004684821,0.0005552313],"category_scores_gemma":[0.0009205628,0.0004797746,0.0002074335,0.0003336691,0.0006720045,0.0002124513,0.0002523221,0.0008203675,0.0002180484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002986592,"about_ca_system_score_gemma":0.0002343095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06538022,"about_ca_topic_score_gemma":0.04907601,"domain_scores_codex":[0.9909284,0.006332207,0.0006387578,0.001027504,0.0004452963,0.000627863],"domain_scores_gemma":[0.9944018,0.002690106,0.0005080996,0.001310715,0.0006842242,0.0004050419],"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":[0.00003026536,0.0002752892,0.06223702,0.0002391958,0.0001003481,0.00004067316,0.006651131,0.0009200983,0.000180442,0.007349816,0.009594095,0.9123816],"study_design_scores_gemma":[0.0009683167,0.00000126686,0.2424261,0.002550016,0.0001081376,0.00009652154,0.0001919852,0.2004533,0.002071382,0.003661911,0.546433,0.001038131],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7343509,0.02067661,0.01191342,0.02654341,0.00165833,0.0005707718,0.0003753778,0.0002222102,0.2036889],"genre_scores_gemma":[0.8472453,0.007844227,0.05738671,0.0002807288,0.0002668052,0.000002563459,0.001872306,0.0000373546,0.08506404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9113435,"threshold_uncertainty_score":0.9997654,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2023934380","doi":"10.1016/j.egypro.2011.03.305","title":"Canadian experience in low carbon eco-city development and the implications for China","year":2011,"lang":"en","type":"article","venue":"Energy Procedia","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Urbanization; China; Urban planning; Environmental planning; Environmental degradation; Environmental protection; Geography; Climate change; Population; Business; Natural resource economics; Environmental resource management; Environmental science; Economic growth; Ecology; Civil engineering; Engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.0210875414417167,"gpt":0.200077636271768,"spread":0.1789900948300513,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001049083,0.00005766299,0.0000641918,0.00003260492,0.0001270941,0.00001663179,0.00008185971,0.00003051008,0.00002011292],"category_scores_gemma":[0.00002787892,0.00003603733,0.00000971122,0.00007958351,0.00004392373,0.00003430403,0.000003001011,0.0000338369,8.677998e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005943846,"about_ca_system_score_gemma":0.0001349207,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3989103,"about_ca_topic_score_gemma":0.8601057,"domain_scores_codex":[0.9995676,0.00001186109,0.00008640985,0.0001268278,0.00003238519,0.0001748905],"domain_scores_gemma":[0.9997632,0.00003178208,0.00002006379,0.00007754096,0.00001125836,0.00009615919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006728706,0.000008270336,0.7324044,0.00001111256,0.000008594705,0.000002657335,0.0219814,0.0001503864,0.000002599084,0.001793581,0.00008228049,0.2434875],"study_design_scores_gemma":[0.0002318103,0.00000957769,0.9888414,0.000006977178,0.000001631516,0.000005508858,0.0001128985,0.004202715,0.0001473732,0.001377743,0.004985667,0.00007672502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983305,0.0001496489,0.00004420576,0.0002828517,0.00007707324,0.00007188747,0.00000450475,0.000009607409,0.01605524],"genre_scores_gemma":[0.9987354,0.00003112612,0.0008205693,0.0001730923,0.00003052447,0.00000292358,0.00001555463,0.000001541725,0.0001893124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4611954,"threshold_uncertainty_score":0.6050924,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2035158728","doi":"10.5558/tfc79233-2","title":"Ecological classification for mountain forest sustainability in northeast China","year":2003,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Chinese Academy of Sciences; Purdue University","keywords":"China; Geography; Sustainability; Vegetation (pathology); Forestry; Ecology; Forest ecology; Ecosystem; Environmental resource management; Land use; Agroforestry; Environmental science; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.01702980241794265,"gpt":0.2413217170405673,"spread":0.2242919146226246,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006276017,0.00009814579,0.0001114599,0.00002514931,0.0002109117,0.00004169932,0.0001541579,0.00007290886,0.0001354984],"category_scores_gemma":[0.0002335829,0.00005842511,0.00005355767,0.000154269,0.0001145419,0.00008359885,0.000004570806,0.0001397628,0.00002258788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004200137,"about_ca_system_score_gemma":0.0001537495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001455365,"about_ca_topic_score_gemma":0.0170461,"domain_scores_codex":[0.999042,0.0001271262,0.0001750028,0.000202982,0.0001004392,0.0003524496],"domain_scores_gemma":[0.9994275,0.0001800592,0.00004880868,0.0002562717,0.00002895718,0.00005842823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006737099,0.00004983064,0.9628097,0.00001990282,0.000004057536,0.000003226059,0.0001525689,0.01910945,0.000002847548,0.003007882,0.0001999841,0.01457313],"study_design_scores_gemma":[0.0003852745,0.0001161761,0.8835683,0.000003653428,0.000004364413,0.0000100919,0.0002881658,0.08994591,0.00001008298,0.02137143,0.004215328,0.00008122993],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947063,0.0001200947,0.0002407275,0.001085961,0.00009729981,0.0004161525,0.00001285544,0.00002831111,0.003292251],"genre_scores_gemma":[0.9995216,0.00001180244,0.0001395724,0.00006353216,0.00005862681,0.000002257822,0.0000419729,0.00000323066,0.0001574188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07924145,"threshold_uncertainty_score":0.9512125,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103651093","doi":"10.1109/tbme.2009.2025962","title":"Effect of Vergence Adaptation on Convergence–Accommodation: Model Simulations","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Accommodation; Vergence (optics); Convergence (economics); Adaptation (eye); Computer science; Artificial intelligence; Optics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01128145054441344,"gpt":0.2222481206602723,"spread":0.2109666701158588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001203111,0.0001118924,0.0001321478,0.0001590978,0.00007474706,0.000009779949,0.00006944058,0.00007636944,0.0002099759],"category_scores_gemma":[0.00001475305,0.00008950037,0.00006182762,0.0002885442,0.00002401888,0.00008568852,9.251527e-8,0.000151107,0.00004277941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006296515,"about_ca_system_score_gemma":0.00001884111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005645539,"about_ca_topic_score_gemma":0.0000116395,"domain_scores_codex":[0.9992332,0.00002603755,0.0001847314,0.0001455431,0.0002646869,0.0001458029],"domain_scores_gemma":[0.9995137,0.0002169231,0.00002902803,0.0001126594,0.0000179544,0.0001096755],"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":[0.00004621164,0.00002139349,0.000007986186,0.000007887052,0.000006535998,0.000001198126,0.00004432557,0.8304349,0.0005958498,0.000003787562,0.000007238847,0.1688227],"study_design_scores_gemma":[0.0002498117,0.0007053229,0.0006727522,0.00004149762,0.00001550192,0.000002026637,0.000003337764,0.9927987,0.005308439,0.00001411992,0.00009707561,0.0000913715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3561712,0.00001165045,0.6429126,0.0001059444,0.0004390822,0.00008217292,0.00003321074,0.00006773843,0.0001764784],"genre_scores_gemma":[0.9986945,0.00002658562,0.001131388,0.00004367769,0.00003617102,1.901382e-7,0.00002850673,0.0000028968,0.00003607177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6425233,"threshold_uncertainty_score":0.3649719,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3120282119","doi":"10.18280/ts.370613","title":"Feature Extraction and Image Retrieval of Landscape Images Based on Image Processing","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Southeast University; National Natural Science Foundation of China","keywords":"Color quantization; Computer science; Artificial intelligence; Image retrieval; Computer vision; Color image; Feature extraction; Feature (linguistics); Matching (statistics); Pattern recognition (psychology); Image processing; Image (mathematics); Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01244827335531389,"gpt":0.2200024489116594,"spread":0.2075541755563455,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001634401,0.00012025,0.0001472787,0.00004733267,0.00009365808,0.00008558679,0.00005963983,0.00004693824,0.0006042829],"category_scores_gemma":[0.00002776427,0.00008939587,0.00004003607,0.0001392318,0.00005371111,0.0001818093,0.000002993803,0.0001412256,0.00001480514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000154047,"about_ca_system_score_gemma":0.0000293088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003016531,"about_ca_topic_score_gemma":0.000009272088,"domain_scores_codex":[0.999191,0.00005144863,0.0001290405,0.0002151854,0.0002579264,0.0001554088],"domain_scores_gemma":[0.9996329,0.00007010336,0.00008585583,0.00005787251,0.00004048232,0.000112786],"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":[0.006810059,0.0002765485,0.1416406,0.001214303,0.00009056711,0.0003734906,0.002587727,0.006536373,0.293768,0.00000805853,0.02542988,0.5212644],"study_design_scores_gemma":[0.001821473,0.001078384,0.4553249,0.0001252708,0.00006574195,0.00001838331,0.0003415093,0.506211,0.03152249,0.00002545382,0.003135772,0.0003295805],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836808,0.0003167808,0.00285963,0.004955974,0.00007396803,0.0002073002,0.000104544,0.00008052151,0.007720437],"genre_scores_gemma":[0.9948011,0.00001798884,0.00445937,0.0004415373,0.0001648586,5.022956e-8,0.00007653519,0.000004271666,0.0000342546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5209348,"threshold_uncertainty_score":0.6616474,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4819806","doi":"10.1139/o74-024","title":"Detecting Vegetation Recovery Patterns After Hurricanes in South Florida Using NDVI Time Series","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Biochemistry","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Normalized Difference Vegetation Index; Vegetation (pathology); Environmental science; Mangrove; Time series; Physical geography; Satellite imagery; Climatology; Climate change; Remote sensing; Geography; Geology; Oceanography; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.008400170324074373,"gpt":0.1798590679078819,"spread":0.1714588975838076,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000220313,0.00008367915,0.0001183098,0.0001053076,0.00006187973,0.00005399886,0.00006745305,0.00006836376,0.0002330695],"category_scores_gemma":[0.00006951829,0.00007321861,0.00004771871,0.0001063751,0.00002714971,0.0002225867,0.000001436334,0.0001562572,0.00001364777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002634112,"about_ca_system_score_gemma":0.0002604018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005851458,"about_ca_topic_score_gemma":0.01149181,"domain_scores_codex":[0.9993294,0.00002769022,0.0002000578,0.00006928561,0.00008845054,0.0002851471],"domain_scores_gemma":[0.9993983,0.00002359666,0.0001189751,0.0000699407,0.00003524045,0.0003539413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002247393,0.000001394211,0.9873694,0.00002950603,0.0000108141,0.0001034282,0.0009564424,0.0007669051,0.001027679,2.038417e-8,0.00001615303,0.00969574],"study_design_scores_gemma":[0.0003214687,0.00006710218,0.9695475,0.0005069881,0.00004183261,0.001117622,0.00159287,0.001678563,0.02424171,0.00002847096,0.0004772403,0.0003786257],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980062,0.001156766,0.00001569176,0.00002963346,0.0003768339,0.00001595778,0.00001724173,0.000002485214,0.0003791713],"genre_scores_gemma":[0.9989697,0.000005811272,0.0003946426,0.00005996239,0.000497458,1.695276e-8,0.00000675615,0.000003537699,0.00006212376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02321403,"threshold_uncertainty_score":0.8845693,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407687667","doi":"10.1016/j.compag.2025.110008","title":"JuDifformer: Multimodal fusion model with transformer and diffusion for jujube disease detection","year":2025,"lang":"en","type":"article","venue":"Computers and Electronics in Agriculture","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Tsinghua University; Energy Council of Canada; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Fusion; Transformer; Artificial intelligence; Computer science; Biological system; Nuclear engineering; Engineering; Biology; Electrical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.00326100879860157,"gpt":0.1803785378050538,"spread":0.1771175290064523,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005915542,0.0001234777,0.0001246019,0.00005346232,0.0001942712,0.00005538969,0.00004151609,0.00006842852,9.196366e-7],"category_scores_gemma":[0.000003048844,0.00006945465,0.00002569564,0.0001265798,0.00002231763,0.00008131431,0.000003912575,0.0001340186,1.917223e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009764785,"about_ca_system_score_gemma":0.00002685889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001641382,"about_ca_topic_score_gemma":0.005482524,"domain_scores_codex":[0.9993627,0.00001238765,0.00009534891,0.0002320674,0.00006814529,0.0002293427],"domain_scores_gemma":[0.9997902,0.00003779461,0.00002114092,0.00005390493,0.00002038329,0.00007659326],"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":[0.000787071,0.00005301975,0.01821584,0.0001391099,0.0000273707,0.000004659902,0.0004408043,0.03494542,0.001262062,0.0001966504,0.0005616791,0.9433663],"study_design_scores_gemma":[0.0009654909,0.0001674322,0.1026017,0.00007301228,0.00002693791,0.000008263853,0.00003591089,0.8920108,0.00009549929,0.001149205,0.00271994,0.000145823],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9591761,0.001846484,0.03774969,0.0005567037,0.00008194851,0.0002745341,0.000009496478,0.00002403355,0.0002810403],"genre_scores_gemma":[0.9967767,0.00133291,0.001392958,0.0001748065,0.00002984383,8.486214e-7,0.00005865993,0.000001926373,0.0002313603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9432205,"threshold_uncertainty_score":0.3059377,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115799842","doi":"10.1109/igarss.2001.977932","title":"Texture analysis for urban spatial pattern study using SPOT imagery","year":2002,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Panchromatic film; Texture (cosmology); Artificial intelligence; Beijing; Pattern recognition (psychology); Computer science; Image texture; Computer vision; Cartography; Image (mathematics); Geography; Image processing","retraction":null,"screen_n_in":null,"score":{"opus":0.03539706861284547,"gpt":0.2315288259872576,"spread":0.1961317573744121,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001336626,0.000108346,0.0001916096,0.0001280837,0.0001527845,0.00009324875,0.00008366761,0.00003975116,0.003448682],"category_scores_gemma":[0.00001408094,0.00007339819,0.0001257135,0.0002781161,0.00001626241,0.00007699852,0.00000378317,0.0000630036,0.00006884271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001868896,"about_ca_system_score_gemma":0.000004407871,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01950552,"about_ca_topic_score_gemma":0.01928263,"domain_scores_codex":[0.9991923,0.00004538114,0.0001530684,0.0002357549,0.0001531073,0.0002204189],"domain_scores_gemma":[0.9995877,0.00007725164,0.00004334242,0.0001841588,0.00002760006,0.00007990828],"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":[0.000008071862,0.00003587378,0.8561599,0.000002554914,0.0001269721,0.0000146124,0.0003500501,0.002492125,0.000004710796,6.627437e-8,0.0007704767,0.1400346],"study_design_scores_gemma":[0.0001966886,0.00008147377,0.4267719,0.000001442584,0.0001901189,0.000002771524,0.0001938692,0.5717314,0.000007695209,0.000003852502,0.0007170136,0.0001016869],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801988,0.00008307102,0.01643767,0.00008900966,0.0001762851,0.000184836,0.00003178449,0.0000426884,0.002755876],"genre_scores_gemma":[0.9977477,0.000003628609,0.0005950858,0.0001781163,0.0002518946,5.854905e-8,0.00004000372,0.000002842262,0.001180687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5692393,"threshold_uncertainty_score":0.9986129,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2119049971","doi":"10.5539/cis.v2n2p137","title":"Based on Delaunay Triangulation DEM of Terrain Model","year":2009,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Digital elevation model; Terrain; Terrain rendering; Computer science; Elevation (ballistics); Raised-relief map; Geographic information system; Remote sensing; Computer graphics (images); Computer vision; Geology; Cartography; Geography; Geometry; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01115080197114099,"gpt":0.2138600981450025,"spread":0.2027092961738615,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003537688,0.00004662266,0.00006087302,0.0001696096,0.0001122977,0.00007944339,0.00008753851,0.00001885957,0.00001028124],"category_scores_gemma":[0.00001916567,0.00003307308,0.00001463568,0.0002437707,0.00006634909,0.001382113,0.000002644302,0.00003277318,0.00000977667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001933664,"about_ca_system_score_gemma":0.00004584295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000184304,"about_ca_topic_score_gemma":0.000002242951,"domain_scores_codex":[0.9994493,0.000009761467,0.0001531892,0.00006894823,0.000222849,0.00009602405],"domain_scores_gemma":[0.9997095,0.00002762793,0.00006045543,0.00009077801,0.00005343223,0.00005821245],"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":[0.00001497089,0.000002942485,0.001166133,0.000002477864,2.514023e-7,7.405617e-8,0.0004020898,0.3512964,0.00001449991,0.0002047936,0.00007427566,0.6468211],"study_design_scores_gemma":[0.0001485524,0.0001027084,0.2050073,0.00000897273,7.70939e-7,0.000001358617,0.00000656458,0.7942082,0.00008982085,0.0001853952,0.0002030703,0.0000373148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6627645,0.000008155688,0.3147922,0.0003201489,0.0001385071,0.00008811874,0.000006781634,0.00002889711,0.02185271],"genre_scores_gemma":[0.9873569,0.000003762633,0.01125208,0.001352867,0.00001626098,1.220066e-8,0.0000133979,2.160439e-7,0.000004511388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6467838,"threshold_uncertainty_score":0.1348681,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3027732676","doi":"10.18280/ts.370218","title":"An Automatic Method for Unsupervised Feature Selection of Hyperspectral Images Based on Fuzzy Clustering of Bands","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Hyperspectral imaging; Pattern recognition (psychology); Artificial intelligence; Feature selection; Computer science; Cluster analysis; Feature (linguistics); Selection (genetic algorithm); Fuzzy logic; Fuzzy clustering; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.01953225436512061,"gpt":0.2489957344924756,"spread":0.229463480127355,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002400449,0.0001087978,0.0002024602,0.00006054578,0.00005770251,0.00002068604,0.00008944935,0.00004573815,0.0003758739],"category_scores_gemma":[0.00001562882,0.00008365396,0.00008332623,0.0001465533,0.0000184877,0.00007325831,0.000001372026,0.00006930784,0.000001429754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003140763,"about_ca_system_score_gemma":0.00003229366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001425045,"about_ca_topic_score_gemma":0.00006842769,"domain_scores_codex":[0.9991983,0.00009479575,0.0001826899,0.0001791518,0.0001917514,0.0001533074],"domain_scores_gemma":[0.9995955,0.0001299422,0.00007748767,0.00006721811,0.00004106998,0.00008881064],"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":[0.001654598,0.0002013543,0.02548919,0.0007206176,0.0001158249,0.000006185262,0.002447846,0.5493881,0.1173978,0.00002135166,0.001105255,0.3014519],"study_design_scores_gemma":[0.0008673262,0.001590072,0.05057136,0.00003274588,0.00003867915,0.000001683262,0.0001303085,0.9306995,0.01588182,0.0000209247,0.00007257028,0.00009303028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9074185,0.00004099797,0.0894105,0.001161373,0.0000908622,0.0004217227,0.0001566902,0.00008622318,0.001213149],"genre_scores_gemma":[0.9198403,0.000001844489,0.07969739,0.0002637838,0.0001046233,2.957848e-7,0.00008022763,0.000004307896,0.000007176855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3813114,"threshold_uncertainty_score":0.4115556,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2077993948","doi":"10.5539/jgg.v1n1p26","title":"The Disaster of May 12th Wenchuan Earthquake and Its Influence on Debris Flows","year":2009,"lang":"en","type":"article","venue":"Journal of Geography and Geology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Quake (natural phenomenon); Geology; Debris; Debris flow; Seismology; Mining engineering; Oceanography","retraction":null,"screen_n_in":null,"score":{"opus":0.005818807608986926,"gpt":0.2014705961778013,"spread":0.1956517885688143,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003227348,0.0000792225,0.0001695555,0.0001072893,0.0001358983,0.00002465061,0.0000826259,0.00005634069,0.00003270041],"category_scores_gemma":[0.00004221849,0.00004172955,0.00006188964,0.00009372002,0.0001159484,0.00008436081,0.000003753263,0.0001616707,0.000002316868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":2.457863e-7,"about_ca_system_score_gemma":0.00001080401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001052772,"about_ca_topic_score_gemma":0.0003458624,"domain_scores_codex":[0.9993291,0.00007554776,0.0002331868,0.00008392718,0.000116151,0.0001621143],"domain_scores_gemma":[0.9994068,0.0002085767,0.0001631128,0.00007305339,0.00005853453,0.00008991584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002596731,0.00001505541,0.6896098,0.000005862059,0.00003497185,0.00002893915,0.0002577269,0.0005794818,0.00003956562,0.00007746235,0.00007768072,0.3090138],"study_design_scores_gemma":[0.0002640854,0.00110262,0.9913161,0.00002392564,0.00001588961,0.0002296917,0.00006660691,0.0005020816,0.00002774231,0.001405056,0.004992679,0.00005345686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934781,0.003720312,0.000003295658,0.001554063,0.0001320383,0.00003155736,0.000002697922,0.000002365098,0.001075553],"genre_scores_gemma":[0.9972926,0.002172887,0.00006982023,0.0003708423,0.00005929131,8.208681e-9,7.56091e-7,7.334592e-7,0.00003310415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3089603,"threshold_uncertainty_score":0.1701682,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386810023","doi":"10.3808/jei.202300502","title":"Differences in China Greening Characteristics and its Contribution to Global Greening","year":2023,"lang":"en","type":"article","venue":"Journal of Environmental Informatics","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Greening; Geography; Stock (firearms); China; Environmental resource management; Environmental science; Ecology; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01155819234628409,"gpt":0.2044969545663638,"spread":0.1929387622200797,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002972737,0.00008122931,0.0001742592,0.00009107801,0.00006626205,0.0000484327,0.00007395181,0.0000398848,0.00004642663],"category_scores_gemma":[0.00004764185,0.00006034468,0.00002680645,0.0001327557,0.00001900049,0.0002850412,0.00001673357,0.0001223213,0.0000488638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001359416,"about_ca_system_score_gemma":0.000007960813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002461397,"about_ca_topic_score_gemma":0.00003270913,"domain_scores_codex":[0.9991338,0.00002292307,0.000415729,0.00003675832,0.000217944,0.0001728241],"domain_scores_gemma":[0.9995978,0.00004034076,0.0001987497,0.00003742933,0.000005073842,0.0001205947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003883764,0.000005888487,0.9419616,0.000009811833,0.000009492001,0.00002836502,0.0008420788,0.0005472456,0.0000301978,0.00000410622,0.00002628879,0.05649607],"study_design_scores_gemma":[0.0002480666,0.0001418866,0.945717,0.00005822101,0.000007162328,0.0001095257,0.000361294,0.05297727,0.00001362512,0.00003430967,0.0002597426,0.00007186305],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992774,0.00006454748,0.0001177444,0.0000880271,0.0001663004,0.00005261922,0.00007653255,0.000006194081,0.0001507004],"genre_scores_gemma":[0.9991488,0.0002939971,0.0003788685,0.00008349952,0.00005431933,2.171825e-8,0.00002469967,0.000001125812,0.00001469787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05642421,"threshold_uncertainty_score":0.2460784,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2803647953","doi":"10.3130/jaabe.17.175","title":"A Study of the Forms and Technology of Traditional Granary Buildings in the Middle and Lower Reaches of the Fu River","year":2018,"lang":"en","type":"article","venue":"Journal of Asian Architecture and Building Engineering","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Granary; Architectural engineering; Vernacular; Civil engineering; Architecture; Flexibility (engineering); Vernacular architecture; Engineering; Geography; Archaeology; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01259229848526835,"gpt":0.1807593842116962,"spread":0.1681670857264278,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002746651,0.00006884982,0.000150102,0.0001365444,0.00005342498,0.000008562547,0.0001386749,0.00003671885,0.000001407199],"category_scores_gemma":[0.00004977221,0.00002904473,0.00003223009,0.0002204907,0.0001741496,0.00003962372,0.00001487403,0.0002124608,9.852632e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001212908,"about_ca_system_score_gemma":0.00001091965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000555746,"about_ca_topic_score_gemma":0.0001413842,"domain_scores_codex":[0.9994901,0.00002642693,0.0001931267,0.00006171638,0.0001452605,0.00008333789],"domain_scores_gemma":[0.9996525,0.00009213347,0.000129424,0.00008456663,0.00002241049,0.00001896068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003483019,0.0002709964,0.5539844,0.000380398,0.0003113368,0.00006269693,0.0595464,0.01149178,0.0198992,0.000539732,0.00009027717,0.3530745],"study_design_scores_gemma":[0.000613143,0.0009300358,0.9895573,0.0004457197,0.00005415885,0.0009669177,0.00158483,0.001619301,0.00154943,0.002310324,0.0002856235,0.00008317249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987705,0.0004766487,0.00009684643,0.0004366774,0.00006977283,0.00007034934,0.000003600149,0.000001760873,0.00007384804],"genre_scores_gemma":[0.9985602,0.00002762332,0.001344987,0.00001350531,0.00005005429,3.591158e-8,9.815894e-8,0.000001988265,0.000001506905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4355729,"threshold_uncertainty_score":0.118441,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2372157960","doi":"","title":"Review of Overseas Crop Monitoring Systems with Remote Sensing","year":2010,"lang":"en","type":"article","venue":"Diqiu kexue jinzhan","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Agriculture; Remote sensing; Food security; Crop; Agricultural productivity; Environmental science; Agricultural engineering; Estimation; Business; Geography; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01448134812265976,"gpt":0.227500819899062,"spread":0.2130194717764022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003345837,0.0001472585,0.000286931,0.00005974383,0.0001063091,0.00005626127,0.000114411,0.00006909544,0.00007158036],"category_scores_gemma":[0.00007600772,0.00009985713,0.00005784326,0.0002259959,0.00006623295,0.0001058523,0.000006581383,0.0002389363,0.00004130992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000025292,"about_ca_system_score_gemma":0.0000518205,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007005278,"about_ca_topic_score_gemma":0.0008015409,"domain_scores_codex":[0.9989337,0.00006312024,0.000241513,0.0002260868,0.0002772803,0.0002583042],"domain_scores_gemma":[0.9991642,0.00007694031,0.0001480954,0.0003691028,0.0001015586,0.0001400751],"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":[0.0001497483,0.00002529898,0.1307147,0.007234088,0.0001412013,0.0002605412,0.0004532336,0.001207617,0.00282013,0.00004317381,0.002459794,0.8544905],"study_design_scores_gemma":[0.002341914,0.0009755174,0.3195473,0.05840387,0.0005066831,0.001676296,0.0009622107,0.146734,0.005590593,0.0001841829,0.4607256,0.002351835],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9510841,0.01164537,0.0002545437,0.0001372802,0.002116483,0.0002890175,0.00002438964,0.0000973219,0.03435154],"genre_scores_gemma":[0.9939439,0.002471302,0.002641581,0.0001129539,0.0004473075,1.271321e-8,0.00002662102,0.000008563447,0.000347766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8521386,"threshold_uncertainty_score":0.9996071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2389483589","doi":"","title":"Stability Analysis for Elementary Characters of Hybrid Rice by AMMI Model","year":2002,"lang":"en","type":"article","venue":"Zuo wu xue bao","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"CAE (Canada)","funders":"","keywords":"Ammi; Adaptability; Stability (learning theory); Mathematics; Yield (engineering); Main effect; Grain yield; Interaction; Linear regression; Gene–environment interaction; Statistics; Horticulture; Biology; Genotype; Computer science; Ecology; Genetics; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.02931364038405715,"gpt":0.2044416335223243,"spread":0.1751279931382672,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002225404,0.0001003685,0.0002190709,0.00006422401,0.00008276266,0.00002183159,0.0001154235,0.0000241251,0.0007570435],"category_scores_gemma":[0.00002126694,0.00008082464,0.000142913,0.0002014884,0.00003700492,0.0001147029,0.000004196883,0.00005913326,0.00002340561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004183485,"about_ca_system_score_gemma":0.000008405286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002468427,"about_ca_topic_score_gemma":0.000683571,"domain_scores_codex":[0.9991201,0.00003750658,0.0002218418,0.0002296856,0.0001632411,0.0002275977],"domain_scores_gemma":[0.9994561,0.0001002137,0.00008605319,0.00023509,0.00003382496,0.00008871652],"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":[0.0003680815,0.0004212564,0.718345,0.000244404,0.001346069,0.00001623611,0.001380462,0.05082707,0.002637352,0.00002022421,0.04779305,0.1766007],"study_design_scores_gemma":[0.000290284,0.00007776495,0.05195713,0.000003756848,0.0001979208,0.000001540245,0.00006528985,0.9417533,0.002069211,0.00009239611,0.003338016,0.0001534286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942251,0.0001832149,0.002475401,0.000208483,0.00007051272,0.0001272813,0.0007212096,0.00002192305,0.00196686],"genre_scores_gemma":[0.9973827,0.00007032465,0.001474917,0.0002188837,0.00003254964,2.109697e-7,0.0004493375,0.00000270411,0.0003683726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8909262,"threshold_uncertainty_score":0.8289095,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3186788152","doi":"10.18280/ts.380322","title":"Automatic Extraction of Color Features from Landscape Images Based on Image Processing","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Color image; Color quantization; Color space; Color balance; False color; Color histogram; Image processing; Support vector machine; Pattern recognition (psychology); Color correction; Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.009783556445075085,"gpt":0.2239966820179179,"spread":0.2142131255728428,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001360258,0.0001087498,0.0001551933,0.00005261843,0.00009573361,0.00008703853,0.00006211204,0.0000440106,0.004602344],"category_scores_gemma":[0.00002398197,0.0000821107,0.00005654315,0.0001219702,0.00003054462,0.0001177548,0.000002333669,0.00009509313,0.00003101066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002984163,"about_ca_system_score_gemma":0.00007256676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003023323,"about_ca_topic_score_gemma":0.0002350363,"domain_scores_codex":[0.9991064,0.00008265029,0.0001853933,0.0001937169,0.000280115,0.0001517021],"domain_scores_gemma":[0.9995204,0.0001742174,0.00009502163,0.00009816951,0.00005344138,0.00005878858],"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":[0.0003908318,0.0003546039,0.05782249,0.0002317485,0.00007239372,0.0003089697,0.0007157887,0.02006213,0.04717714,0.000004516034,0.007188883,0.8656705],"study_design_scores_gemma":[0.0005834658,0.0001372656,0.5851393,0.0001178443,0.0000364948,0.000008369444,0.0001950319,0.3955827,0.01765774,0.00004948964,0.0003716968,0.0001206686],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911337,0.0002708588,0.0007228845,0.0003435375,0.0001194052,0.00008453633,0.00009741812,0.00005515747,0.007172455],"genre_scores_gemma":[0.9937943,0.000008554725,0.005492555,0.0002144067,0.0001168673,2.026256e-7,0.0002879312,0.000003609374,0.00008160098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8655499,"threshold_uncertainty_score":0.9963076,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2385552135","doi":"","title":"Response of Plant Functional Traits to Environment and Its Application","year":2008,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Functional ecology; Ecosystem; Ecology; Biology; Trait; Environmental science; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01931590103385784,"gpt":0.1757036821700718,"spread":0.156387781136214,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001018267,0.00003582955,0.00004855978,0.00002891664,0.0000487073,0.000002066185,0.00001928483,0.00001818272,0.0002419425],"category_scores_gemma":[0.000008517083,0.00002551247,0.00000905703,0.00003114989,0.00001334545,0.00002314605,0.000001952814,0.00001886672,0.0001115899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":8.005688e-7,"about_ca_system_score_gemma":0.000008646342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001170918,"about_ca_topic_score_gemma":0.00004995211,"domain_scores_codex":[0.9996577,0.00002381943,0.00006818688,0.00009266176,0.0000965416,0.00006110477],"domain_scores_gemma":[0.9998204,0.00006073537,0.00001391082,0.0000387158,0.000004332479,0.00006193707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008733579,0.000158859,0.4923065,0.00004016816,0.00007265563,0.00005685658,0.003604649,0.04394034,0.07012329,0.0003234335,0.01625727,0.3643824],"study_design_scores_gemma":[0.00009823113,0.00008240653,0.975938,0.000001591663,0.000001559292,0.00003433073,0.00001652164,0.005735599,0.001079247,0.00001067432,0.01696163,0.00004025962],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998013,0.00006321256,0.0005193404,0.0003300897,0.00001767786,0.00006730083,0.00003039446,0.000008547218,0.0009504801],"genre_scores_gemma":[0.9986336,0.00004083566,0.0004647636,0.0001528503,0.00001619898,7.75807e-8,0.00002185872,6.72517e-7,0.0006691862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4836315,"threshold_uncertainty_score":0.26491,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401109758","doi":"10.1109/jstars.2024.3435559","title":"Spatial and Temporal Change Monitoring of Wetland Urban Ecology Based on a Remote Sensing Ecological Index Considering Full Elements","year":2024,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection; National Natural Science Foundation of China; Ministry of Natural Resources","keywords":"Index (typography); Wetland; Remote sensing; Ecology; Environmental science; Change detection; Environmental resource management; Computer science; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.04007944440475792,"gpt":0.2442608146225479,"spread":0.20418137021779,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005402695,0.0001870938,0.0003802392,0.0003820989,0.0001495079,0.00009956262,0.00004970307,0.0001772739,0.000006639827],"category_scores_gemma":[0.00009867625,0.0001513555,0.00004489438,0.000419881,0.00008709809,0.00008536666,0.000009136034,0.0005218083,5.577837e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001778614,"about_ca_system_score_gemma":0.0001346564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009783722,"about_ca_topic_score_gemma":0.003551292,"domain_scores_codex":[0.9984728,0.0001045469,0.0006121074,0.0002425459,0.0002776118,0.0002904492],"domain_scores_gemma":[0.9990632,0.0003384045,0.0002360255,0.000104362,0.00014645,0.0001115515],"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":[0.0002022828,0.00001492163,0.1540741,0.0001232171,0.0000572879,0.0002781967,0.0005208981,0.002489557,0.002938025,0.000006130438,0.0000175572,0.8392779],"study_design_scores_gemma":[0.0005069179,0.0002226883,0.4009931,0.0003743253,0.00002657932,0.0001439478,0.00007247883,0.596311,0.0004734189,0.0003258385,0.0004180973,0.0001315424],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935737,0.0002080948,0.004700476,0.0004125868,0.0006976254,0.0001717513,0.000006042611,0.00002313187,0.0002066054],"genre_scores_gemma":[0.9437088,0.0001921891,0.05536523,0.0001012162,0.0006078322,3.897549e-9,0.000006524477,0.000008326394,0.000009808935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8391463,"threshold_uncertainty_score":0.6172097,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3183470465","doi":"10.14796/jwmm.c475","title":"Urban Tree Rainfall Interception Measurement and Modeling in WinSLAMM, the Source Loading and Management Model","year":2021,"lang":"en","type":"article","venue":"Journal of Water Management Modeling","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Interception; Environmental science; Tree (set theory); Hydrology (agriculture); Geology; Mathematics; Geotechnical engineering; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.04836920439842873,"gpt":0.2097243525756697,"spread":0.1613551481772409,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001415522,0.0001564132,0.0002071104,0.0002109881,0.0001526625,0.0002179428,0.0001344434,0.00003732315,0.00001060093],"category_scores_gemma":[0.000006044249,0.00009306318,0.00006290847,0.00008587835,0.00001894673,0.0002719724,0.00006821444,0.000203778,0.000002537585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002129954,"about_ca_system_score_gemma":0.000008276486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008338867,"about_ca_topic_score_gemma":0.0003930102,"domain_scores_codex":[0.9984658,0.00008988425,0.0004796109,0.0002265576,0.0004548027,0.0002833672],"domain_scores_gemma":[0.999605,0.00001023621,0.00007681925,0.0001497299,0.00007947823,0.00007874986],"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":[0.00005629881,0.00001283439,0.001035017,0.00007722468,0.00007749832,0.00007432843,0.002077932,0.9161556,0.00008036275,0.00001651936,0.00004551978,0.08029088],"study_design_scores_gemma":[0.0006784747,0.00002725691,0.0004724462,0.0002772509,0.00009941046,0.00005214696,0.002008542,0.9946792,0.00002452438,0.001343145,0.000207572,0.000130045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8094627,0.0008652913,0.1861421,0.0008033451,0.0001199638,0.0001187344,4.461177e-7,0.00000967892,0.002477761],"genre_scores_gemma":[0.9925908,0.001839109,0.00503253,0.0002440819,0.00007928628,1.941346e-7,0.000003546302,0.000007005856,0.0002034564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1831281,"threshold_uncertainty_score":0.3795006,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2055152255","doi":"10.5539/jgg.v2n1p58","title":"Detecting Vegetation Change in Neka River Basin of IRAN Based on","year":2010,"lang":"en","type":"article","venue":"Journal of Geography and Geology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Woodland; Normalized Difference Vegetation Index; Land use; Geography; Physical geography; Land cover; Drainage basin; Vegetation (pathology); Agriculture; Land degradation; Fragmentation (computing); Land use, land-use change and forestry; Environmental science; Hydrology (agriculture); Climate change; Geology; Ecology; Cartography; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.01242082945448549,"gpt":0.2160390679867201,"spread":0.2036182385322347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004029435,0.00005466546,0.0001480252,0.0003562855,0.00003577127,0.000006121412,0.00004649988,0.0000737357,0.00005553565],"category_scores_gemma":[0.00004626377,0.00003900733,0.00005746657,0.0001396087,0.00009073784,0.00006985942,0.000001591529,0.0002427071,0.000001155662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":2.932926e-7,"about_ca_system_score_gemma":0.000008412294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001565312,"about_ca_topic_score_gemma":0.004049755,"domain_scores_codex":[0.9994814,0.00007146448,0.0001870066,0.00006519406,0.00008469474,0.0001102087],"domain_scores_gemma":[0.9995329,0.000170203,0.0001629524,0.00005092758,0.00003560035,0.00004746186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008913441,0.00001101838,0.8236404,0.000007755835,0.000004311932,0.00001669458,0.0002147365,0.0002604669,0.00005499446,0.000003449039,0.000001489121,0.1756956],"study_design_scores_gemma":[0.0004737154,0.000439857,0.990082,0.00003056971,0.000008284288,0.00004665061,0.00002634145,0.008099033,0.0000741396,0.0004511126,0.0002260877,0.0000422649],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982918,0.0002062481,0.00002347616,0.0002936485,0.0003597301,0.00002997963,9.982198e-7,0.000002050463,0.0007921079],"genre_scores_gemma":[0.9987517,0.00005152439,0.0008597581,0.0002313329,0.0001021582,1.879863e-8,0.000001386529,9.414521e-7,0.000001156969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1756533,"threshold_uncertainty_score":0.2366293,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2140921326","doi":"10.5539/jsd.v3n2p221","title":"Remote Sensing and Geographic Information System for Inferring Land Cover and Land Use Change in Wuhan (China), 1987-2006","year":2010,"lang":"en","type":"article","venue":"Journal of Sustainable Development","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Land cover; China; Land use; Cultivated land; Geography; Physical geography; Remote sensing; Geographic information system; Environmental science; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.01045469936599206,"gpt":0.198539844815297,"spread":0.188085145449305,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008153143,0.0001099479,0.0001951384,0.0003877919,0.0001707165,0.0002427007,0.00004177822,0.00007592825,0.000003325243],"category_scores_gemma":[0.00008606465,0.00008217707,0.0000216139,0.0001371542,0.00002376881,0.0008305945,0.00001330624,0.0001970331,0.000001075903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001501559,"about_ca_system_score_gemma":0.00009399989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006063451,"about_ca_topic_score_gemma":0.00288812,"domain_scores_codex":[0.9991212,0.00002669152,0.0003405983,0.00008286264,0.0001598222,0.0002687867],"domain_scores_gemma":[0.9994027,0.00007684017,0.0002031563,0.000056859,0.000144567,0.0001158865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001284286,0.000002970389,0.8823861,0.0003403459,0.00001891643,0.0001140447,0.002765733,0.0002712912,0.00000546705,0.000006233926,0.00001604152,0.1139444],"study_design_scores_gemma":[0.0008655628,0.00006128009,0.9640366,0.0001724668,0.00001135603,0.0003671744,0.0007932431,0.02101958,0.0000236455,0.00004155225,0.01247975,0.0001277885],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987387,0.0001444583,0.0004608773,0.000114802,0.0002021813,0.000209219,0.000002955709,0.000008436946,0.0001183581],"genre_scores_gemma":[0.9943321,0.00007162254,0.005386014,0.00006208716,0.00008070633,4.855091e-8,0.000009601211,0.000003039066,0.0000547996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1138166,"threshold_uncertainty_score":0.9166165,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}