{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":81,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":81,"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":"abae08d6db3a","filters":{"venue":"Applied Geography"}},"results":[{"id":"W2007825373","doi":"10.1016/j.apgeog.2011.06.010","title":"Mapping the vulnerability of crop production to drought in Ghana using rainfall, yield and socioeconomic data","year":2011,"lang":"en","type":"article","venue":"Applied Geography","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":379,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Economic and Social Research Council","keywords":"Vulnerability (computing); Geography; Socioeconomic status; Agriculture; Scale (ratio); Adaptive capacity; Production (economics); Vulnerability assessment; Climate change; Agricultural productivity; Environmental resource management; Socioeconomics; Environmental science; Cartography; Population; Ecology; Psychological intervention; Economics; Environmental health","retraction":null,"screen_n_in":null,"score":{"opus":0.1267351743354609,"gpt":0.2599033728836824,"spread":0.1331681985482216,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005215326,0.0001150152,0.0001595493,0.00002860459,0.0001251396,0.00002672035,0.0003427591,0.00007125226,0.0001169869],"category_scores_gemma":[0.00003609417,0.00003984363,0.00003328659,0.0004433715,0.0001068847,0.0001221081,0.0002448976,0.0001165332,0.000003684101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001193567,"about_ca_system_score_gemma":0.000002855331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001501253,"about_ca_topic_score_gemma":0.002593565,"domain_scores_codex":[0.999101,0.00002540764,0.000209451,0.0003706414,0.00007962566,0.0002138102],"domain_scores_gemma":[0.999571,0.00007817698,0.00009702872,0.0001746299,0.00002401951,0.00005515198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001045483,0.0002586232,0.2103791,0.00005130848,0.00005503619,9.479454e-7,0.006725653,0.0000100865,0.7221318,0.0001861686,0.0008892615,0.05920747],"study_design_scores_gemma":[0.00007360198,0.00004350505,0.9872419,0.00002170754,0.00001101442,0.000003046709,0.006512176,0.00001605028,0.004655499,0.0006661091,0.0005821295,0.0001732795],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977265,0.00009842325,0.000002265236,0.001113524,0.00005676778,0.0004708564,0.00004996505,0.00002067076,0.0004610408],"genre_scores_gemma":[0.9992807,0.00002556328,0.0002829549,0.0002548549,0.0001042217,0.00001508752,0.00003236755,8.489974e-7,0.00000343678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7768628,"threshold_uncertainty_score":0.2269456,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021596910","doi":"10.1016/j.apgeog.2013.06.007","title":"Crime seasonality and its variations across space","year":2013,"lang":"en","type":"article","venue":"Applied Geography","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":190,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Seasonality; Variation (astronomy); Geography; Space (punctuation); Ecology; Biology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02479570293447609,"gpt":0.3311752850822035,"spread":0.3063795821477274,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002636322,0.00007409523,0.00008531746,0.00002922817,0.0006465808,0.0001871918,0.0001196334,0.00005850646,0.002319938],"category_scores_gemma":[0.00001857847,0.00007438303,0.00008647693,0.0002572707,0.0001343483,0.0001527241,0.00005554626,0.00007938784,0.0002729709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009003343,"about_ca_system_score_gemma":0.00001292769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003666924,"about_ca_topic_score_gemma":0.0003037053,"domain_scores_codex":[0.9992229,0.00003757246,0.0001110177,0.0001876806,0.0001663895,0.0002744627],"domain_scores_gemma":[0.9995881,0.00004432248,0.00004497573,0.000115267,0.00007874708,0.0001286197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000002634665,0.0001369784,0.06395195,0.00001579984,0.00005945696,2.987849e-7,0.005130631,5.981501e-7,0.0006943833,0.9176118,0.007217617,0.005177887],"study_design_scores_gemma":[0.0001912407,0.00001332697,0.9099023,0.000007697818,0.00001893953,2.490766e-7,0.003009416,0.00001846524,0.0001109039,0.01864334,0.06791943,0.0001646918],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8146914,0.0002878514,0.0006772292,0.002447115,0.0001203264,0.0004667228,0.00004155172,0.0001157916,0.181152],"genre_scores_gemma":[0.9986421,0.00004424235,0.0001858396,0.0002208062,0.00008457778,0.0001030526,0.000007402453,0.000005729534,0.0007062632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8989684,"threshold_uncertainty_score":0.9985921,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2996915344","doi":"10.1016/j.apgeog.2019.102135","title":"Linking climate change and socioeconomic development to urban land use simulation: Analysis of their concurrent effects on carbon storage","year":2020,"lang":"en","type":"article","venue":"Applied Geography","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":148,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"China Sponsorship Council; National Natural Science Foundation of China","keywords":"Urbanization; Climate change; Land use, land-use change and forestry; Land use; Environmental science; Geography; Representative Concentration Pathways; Land cover; Context (archaeology); Environmental resource management; Greenhouse gas; Carbon sequestration; Environmental protection; Ecology; Climate model; Carbon dioxide; Engineering; Civil engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01722229174600549,"gpt":0.2097584453419537,"spread":0.1925361535959482,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009867005,0.0001251493,0.0002446037,0.00008962847,0.00007206518,0.00002756946,0.00008708963,0.00004095183,0.00003576813],"category_scores_gemma":[7.887049e-7,0.0001001077,0.00005634631,0.0003017028,0.000009392018,0.00005176947,0.0001125619,0.00004440499,0.000031719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001815209,"about_ca_system_score_gemma":0.000001414269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006470459,"about_ca_topic_score_gemma":0.0001760677,"domain_scores_codex":[0.9992657,0.00001623902,0.0001684229,0.0002763846,0.0001043154,0.0001689376],"domain_scores_gemma":[0.9995984,0.00009365648,0.00008589352,0.0001087717,0.000002933745,0.0001103267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002430064,0.00001692416,0.9739259,0.00006211493,0.0001575517,7.66671e-7,0.003307206,0.01407655,0.0001102552,0.000008803097,0.000002618491,0.008306939],"study_design_scores_gemma":[0.0003031198,0.00007191058,0.9702135,0.00002317717,0.0001494068,4.041052e-8,0.00004059599,0.02695286,0.0005890016,0.00000435293,0.001466711,0.0001852738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991986,0.00005922382,0.00002506493,0.00005087162,0.00003224617,0.000314104,0.00001612987,0.0000246106,0.0002791778],"genre_scores_gemma":[0.9991719,0.00002562964,0.00005360261,0.0006285072,0.00003962321,0.00004216519,0.0000308014,0.000007679188,1.348098e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01287631,"threshold_uncertainty_score":0.4082275,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1995091740","doi":"10.1016/j.apgeog.2008.12.004","title":"Testing for similarity in area-based spatial patterns: A nonparametric Monte Carlo approach","year":2009,"lang":"en","type":"article","venue":"Applied Geography","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":137,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Nonparametric statistics; Similarity (geometry); Spatial analysis; Monte Carlo method; Point (geometry); Spatial ecology; Index (typography); Data mining; Computer science; Variety (cybernetics); Geography; Cartography; Statistics; Mathematics; Artificial intelligence; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.04088673232003914,"gpt":0.2143728825399187,"spread":0.1734861502198796,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004651968,0.0002361166,0.0005534168,0.001163551,0.0001064708,0.00009114498,0.0003184857,0.0001470952,0.00003616961],"category_scores_gemma":[0.0001053722,0.000268636,0.0002524707,0.001653495,0.00003187533,0.00008668904,0.00002582493,0.0001821956,0.00001682693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000313555,"about_ca_system_score_gemma":0.00001191398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005478439,"about_ca_topic_score_gemma":0.0002510813,"domain_scores_codex":[0.9982074,0.000008996661,0.0006207683,0.0006572321,0.00006228052,0.0004432951],"domain_scores_gemma":[0.9990202,0.000136306,0.0002833255,0.0004339024,0.00003448954,0.00009181931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005624154,0.0004050622,0.969433,0.00004415449,0.00005529328,0.000002303423,0.00005877699,0.005255423,0.000016897,0.002231048,0.00008281347,0.02235896],"study_design_scores_gemma":[0.001421421,0.0001523664,0.8713872,0.00001138986,0.00003164286,4.427503e-7,0.00003199179,0.1170245,0.00003966985,0.008724207,0.0007147164,0.0004604055],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7914966,0.0006753604,0.192513,0.0002282406,0.0001256567,0.001246535,0.001331492,0.0001286849,0.01225448],"genre_scores_gemma":[0.9893829,0.000009816158,0.009358876,0.0007201514,0.000087742,0.0001835077,0.0002349405,0.00001725545,0.000004828417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1978863,"threshold_uncertainty_score":0.9999766,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008392531","doi":"10.1016/j.apgeog.2005.08.001","title":"Multi-criteria evaluation and least cost path analysis for an arctic all-weather road","year":2005,"lang":"en","type":"article","venue":"Applied Geography","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":122,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Aboriginal Affairs Northern Dev Canada; University of Waterloo; Queen's University","funders":"","keywords":"Weighting; Port (circuit theory); Transport engineering; Arctic; Path (computing); The arctic; Geography; Computer science; Environmental science; Civil engineering; Operations research; Environmental resource management; Meteorology; Engineering; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.05352760548534175,"gpt":0.3529958266204327,"spread":0.2994682211350909,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002256395,0.0001657942,0.0002707595,0.0006999325,0.0007378761,0.0001759513,0.0001620991,0.0001114144,0.0001126885],"category_scores_gemma":[0.00004189539,0.0001599763,0.0001826157,0.001232371,0.0002534454,0.0003463527,0.0000301156,0.00006824406,0.00002182118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000375826,"about_ca_system_score_gemma":0.00002558756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001685477,"about_ca_topic_score_gemma":0.005103155,"domain_scores_codex":[0.9983298,0.0001027934,0.0003502563,0.0003105337,0.0005231065,0.0003835397],"domain_scores_gemma":[0.9989836,0.00006346028,0.0001889143,0.0002414161,0.0003857847,0.0001367959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001429128,0.0005583995,0.5870504,0.0001025205,0.004186527,2.945818e-7,0.1454767,0.0008452692,0.0003781801,0.02579849,0.0007462614,0.234714],"study_design_scores_gemma":[0.00297204,0.00009394296,0.8346523,0.00001751348,0.001950203,7.460872e-7,0.04105043,0.015002,0.0000155415,0.001479547,0.1020191,0.0007466377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.936437,0.001165407,0.01450153,0.001492951,0.0003840892,0.007596831,0.0001219391,0.0004137939,0.03788647],"genre_scores_gemma":[0.9942071,0.0000769918,0.00415956,0.0003430608,0.0001759424,0.0008796474,0.00008789699,0.00001061729,0.00005916192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2476019,"threshold_uncertainty_score":0.6523643,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1977246553","doi":"10.1016/j.apgeog.2014.11.016","title":"Exploring the relationships between post-fire vegetation regeneration dynamics, topography and burn severity: A case study from the Montane Cordillera Ecozones of Western Canada","year":2014,"lang":"en","type":"article","venue":"Applied Geography","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":120,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"National Aeronautics and Space Administration","keywords":"Normalized Difference Vegetation Index; Chronosequence; Vegetation (pathology); Physical geography; Geography; Montane ecology; Common spatial pattern; Regeneration (biology); Environmental science; Forestry; Remote sensing; Climatology; Climate change; Geology; Ecology; Soil science","retraction":null,"screen_n_in":null,"score":{"opus":0.01600066109378634,"gpt":0.1868075218428336,"spread":0.1708068607490472,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000629832,0.00017802,0.0002105912,0.00004157242,0.0005414903,0.00005704207,0.0002044003,0.00004213631,0.000005865118],"category_scores_gemma":[0.00002687417,0.0001220189,0.00004782829,0.0004113948,0.0001237021,0.0001798818,0.0001047245,0.0002106411,0.000003257927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005196483,"about_ca_system_score_gemma":0.000009855525,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6864538,"about_ca_topic_score_gemma":0.8947219,"domain_scores_codex":[0.9984909,0.0003080825,0.0003188501,0.0003319598,0.0003675218,0.0001826626],"domain_scores_gemma":[0.9985645,0.0006823879,0.0001930208,0.0004727407,0.00002016125,0.00006715828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000961319,0.00003433456,0.9769706,0.000009035544,0.00007597968,0.000009371208,0.002037222,0.0003298028,0.00009505874,0.00002738538,0.0000171751,0.0203845],"study_design_scores_gemma":[0.0002841845,0.00008315752,0.989631,0.00001302534,0.0001012459,0.0000145595,0.004459954,0.005010793,0.00006417065,0.0001162554,0.00006722952,0.0001544396],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980742,0.00006010641,0.0002174703,0.0003785298,0.000123221,0.00093417,0.00003354439,0.00002822474,0.000150524],"genre_scores_gemma":[0.9995351,0.000009359268,0.00007999718,0.0000731078,0.00007137831,0.0001637643,0.00004762019,0.00001731988,0.000002337656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2082681,"threshold_uncertainty_score":0.4975786,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025584805","doi":"10.1016/j.apgeog.2014.09.010","title":"Can community gardens and farmers' markets relieve food desert problems? A study of Edmonton, Canada","year":2014,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":110,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Alberta","funders":"","keywords":"Geography; Desert (philosophy); Socioeconomics; Agricultural economics; Economics; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.00592231079280689,"gpt":0.1557783334262628,"spread":0.1498560226334559,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004349379,0.0001739287,0.0002622477,0.00001357228,0.0003424907,0.00002597617,0.0002586606,0.0000696993,0.00003100483],"category_scores_gemma":[0.00001720666,0.00006681099,0.000053343,0.0003372913,0.00008875223,0.00001657923,0.0001225484,0.0002272002,2.504766e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002136675,"about_ca_system_score_gemma":0.00001502196,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4669523,"about_ca_topic_score_gemma":0.9487919,"domain_scores_codex":[0.9987669,0.0002191996,0.0002368705,0.0002496937,0.0002394328,0.0002878904],"domain_scores_gemma":[0.9992725,0.0002426019,0.0001002338,0.0001383595,0.0001140514,0.0001322908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001106433,0.001286406,0.9725575,0.00008001741,0.0002045327,0.000001332116,0.002142265,0.000004530244,0.004359497,0.0003207292,0.005110353,0.01382217],"study_design_scores_gemma":[0.0002732041,0.0007617427,0.9784129,0.000004879831,0.00003670717,8.784444e-7,0.01114471,0.000001111931,0.00009613987,0.001101044,0.007990262,0.0001763776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925828,0.00006746979,2.587289e-7,0.0003259123,0.00002272481,0.0006482347,0.0000218141,0.00003093831,0.006299838],"genre_scores_gemma":[0.9996561,0.000007673079,0.000009666239,0.0001763353,0.00003063235,0.00005078701,0.00002614467,9.720736e-7,0.00004163901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4818396,"threshold_uncertainty_score":0.5365973,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2604212042","doi":"10.1016/j.apgeog.2017.03.018","title":"How do changes in the daily food and transportation environments affect grocery store accessibility?","year":2017,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":107,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Public Health; The Scarborough Hospital; Impact; University of Waterloo; University of Toronto","funders":"","keywords":"Schedule; Extant taxon; Morning; Healthy food; Public transport; Business; Geography; Grocery store; Marketing; Grocery shopping; Environmental health; Advertising; Transport engineering; Medicine; Engineering; Economics; Food science","retraction":null,"screen_n_in":null,"score":{"opus":0.01829416221610107,"gpt":0.2634925917471707,"spread":0.2451984295310696,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007889064,0.0001452707,0.0001665806,0.00008199636,0.001011242,0.0004872976,0.0006182468,0.0001175106,0.00001984381],"category_scores_gemma":[0.00001310516,0.0001099286,0.00006853556,0.0001545443,0.0006852825,0.0004598395,0.00001287514,0.0001626022,0.00000108863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001241174,"about_ca_system_score_gemma":0.00001489475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005409326,"about_ca_topic_score_gemma":0.02655915,"domain_scores_codex":[0.998731,0.00005792734,0.0001208882,0.0004155203,0.0003758541,0.0002988783],"domain_scores_gemma":[0.9992336,0.00006776632,0.0001496195,0.0004714931,0.000008081642,0.00006943026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002398696,0.0000742437,0.9806893,0.00002333564,0.000014623,0.000001972119,0.006731301,1.474799e-7,0.0001285848,0.0014142,0.0000198221,0.01087844],"study_design_scores_gemma":[0.0003670101,0.00003235771,0.9868296,0.000008551379,0.0000289113,2.470151e-8,0.003293971,3.123802e-7,0.0001446186,0.005980525,0.003178102,0.0001360593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940727,0.0003044239,0.00003398824,0.001571108,0.00007682191,0.0006068429,0.00002498186,0.00002450916,0.003284626],"genre_scores_gemma":[0.9993854,0.0001701381,0.00003825757,0.0001307968,0.0001081371,0.000113955,0.00002227957,0.000007958603,0.00002309078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02601822,"threshold_uncertainty_score":0.9912036,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994748144","doi":"10.1016/j.apgeog.2013.02.011","title":"A GIS-based risk rating of forest insect outbreaks using aerial overview surveys and the local Moran's I statistic","year":2013,"lang":"en","type":"article","venue":"Applied Geography","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":83,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria; Natural Resources Canada; Wilfrid Laurier University; Canadian Forest Service","funders":"Natural Resources Canada; Ministry of Forests, Lands and Natural Resource Operations; Government of Canada","keywords":"Mountain pine beetle; Geography; Bivariate analysis; Dendroctonus; Population; Ecology; Forestry; Statistic; Geographic information system; Cartography; Environmental resource management; Bark beetle; Environmental science; Demography; Statistics; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01016473642799484,"gpt":0.2081135182240358,"spread":0.197948781796041,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001204708,0.0001516147,0.0002264977,0.0000551299,0.0002287639,0.00002894276,0.0001721432,0.00006069119,0.0005600746],"category_scores_gemma":[0.00002602142,0.0001075884,0.00006045832,0.0003025701,0.001193033,0.00006706825,0.0001621665,0.0001245343,0.00003762143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001716592,"about_ca_system_score_gemma":0.000007395928,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01809881,"about_ca_topic_score_gemma":0.003042419,"domain_scores_codex":[0.9987476,0.000302534,0.0002592334,0.0002486907,0.0001842831,0.0002576793],"domain_scores_gemma":[0.9991979,0.0003016962,0.0001922949,0.0002453353,0.000008137554,0.00005464631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000195803,0.0002006606,0.877572,0.0001220347,0.0001742956,0.000004221058,0.0004590526,0.05207666,0.0008379387,0.01068993,0.0004602557,0.05720713],"study_design_scores_gemma":[0.001804532,0.00007237027,0.9674181,0.00000877358,0.00007676371,0.000001022938,0.000071553,0.01790133,0.00005974031,0.01234867,0.00008977078,0.0001473836],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9472868,0.00008915425,0.05006865,0.0000220336,0.00007462504,0.000841132,0.0000156342,0.00002198895,0.001579938],"genre_scores_gemma":[0.9975281,0.00003162525,0.002056302,0.000221335,0.00001439083,0.000123071,0.00001024827,0.00001135743,0.000003584265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08984607,"threshold_uncertainty_score":0.9884397,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2801855115","doi":"10.1016/j.apgeog.2018.04.015","title":"Spatiotemporal analysis of regional socio-economic vulnerability change associated with heat risks in Canada","year":2018,"lang":"en","type":"article","venue":"Applied Geography","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":79,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Simon Fraser University; University of Ottawa","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; Simon Fraser University; University of the Pacific; National Science Foundation","keywords":"Vulnerability (computing); Geography; Economic geography; Regional science; Socioeconomics; Environmental planning; Sociology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.06605016869221167,"gpt":0.2884618629084549,"spread":0.2224116942162433,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003276225,0.0001275426,0.0003129467,0.0001565397,0.00009358716,0.000006179805,0.0001289986,0.00006120393,0.001315938],"category_scores_gemma":[0.000004937561,0.0001143164,0.00005969281,0.000915295,0.0002557301,0.00006735425,0.0000488498,0.0001006168,0.00001338675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006254082,"about_ca_system_score_gemma":0.00007940246,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9700371,"about_ca_topic_score_gemma":0.994675,"domain_scores_codex":[0.9988133,0.00003577685,0.0002640658,0.0002969099,0.00023275,0.0003572504],"domain_scores_gemma":[0.999415,0.00007583415,0.0001329536,0.000235436,0.000009282333,0.0001315133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004348064,0.00004294054,0.9977503,0.000003998404,0.00007127719,8.04017e-7,0.0004686578,0.0001818926,0.00002614542,0.00001361319,0.0004258441,0.0009710825],"study_design_scores_gemma":[0.0003229013,0.00006037936,0.9981992,0.000007387717,0.00007948581,1.094355e-7,0.0002155246,0.0006670177,0.00005984435,0.0001357942,0.0001255429,0.0001268426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974622,0.00001775063,0.000003311141,0.0004430684,0.00002953971,0.0002662727,0.00009755971,0.00001074034,0.001669634],"genre_scores_gemma":[0.9989226,0.00002178063,0.0000391819,0.0008094377,0.00003374636,0.00004866269,0.0001150096,0.000007998202,0.000001521571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02463787,"threshold_uncertainty_score":0.999597,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4238021679","doi":"10.4324/9780203012512-20","title":"Water supply and management","year":2002,"lang":"en","type":"book-chapter","venue":"Applied Geography","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Business; Environmental science","retraction":null,"screen_n_in":null,"score":{"opus":0.01040983639097536,"gpt":0.2027474940671921,"spread":0.1923376576762167,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002923659,0.000385745,0.0003211273,0.0005040705,0.0005918073,0.0002590528,0.0004082173,0.0002506707,0.00284448],"category_scores_gemma":[2.355413e-7,0.0003353051,0.0001870247,0.00005450207,0.0007325932,0.00004811475,0.0002007801,0.0002480131,0.0008019774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003760608,"about_ca_system_score_gemma":0.000003969154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001452239,"about_ca_topic_score_gemma":0.000138537,"domain_scores_codex":[0.9978104,0.00001700583,0.000271196,0.0006372792,0.0006662125,0.0005979552],"domain_scores_gemma":[0.9993036,0.00001549208,0.00006274413,0.0004152647,0.00002031724,0.0001825763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001260935,0.00002335445,0.0001790515,0.0001380498,0.0004067337,0.00004061245,0.003263324,0.00000116642,0.000001879392,0.9374058,0.006695331,0.05183204],"study_design_scores_gemma":[0.0002802952,0.0000162835,0.0002248606,0.0000378478,0.0001823935,4.229916e-7,0.0001289189,1.459905e-7,0.000006854186,0.04219464,0.9564975,0.0004298406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001215392,0.0003618115,0.00004490657,0.001055707,0.0001415269,0.0011873,0.00001597618,0.000232974,0.9968383],"genre_scores_gemma":[0.03243153,0.008614205,0.0009903155,0.001263053,0.0004243319,0.0002006257,0.0001200254,0.0001489412,0.955807],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9498022,"threshold_uncertainty_score":0.999976,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2802408029","doi":"10.1016/j.apgeog.2018.04.016","title":"Routine activity, population(s) and crime: Spatial heterogeneity and conflicting Propositions about the neighborhood crime-population link","year":2018,"lang":"en","type":"article","venue":"Applied Geography","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":72,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"International Centre for Comparative Criminology; Université de Montréal","funders":"","keywords":"Census; Proposition; Census tract; Geography; Population; Geographically Weighted Regression; Criminology; Cartography; Demography; Sociology; Regional science; Statistics; Epistemology; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02550414180249791,"gpt":0.3405846199043447,"spread":0.3150804781018468,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004064005,0.0001370234,0.0001435173,0.0001095841,0.001945363,0.0002638388,0.0001170313,0.00009720266,0.0001805843],"category_scores_gemma":[0.00002807222,0.0001148525,0.00009066813,0.0002480272,0.0004041677,0.0001734669,0.00009455503,0.0001459123,0.000008183321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001732583,"about_ca_system_score_gemma":0.00001098266,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02355264,"about_ca_topic_score_gemma":0.005908476,"domain_scores_codex":[0.9988713,0.0001093963,0.0002150484,0.0003076793,0.0002284853,0.0002680537],"domain_scores_gemma":[0.9994032,0.00007147835,0.0001443344,0.0001956043,0.00008608146,0.00009924755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003031555,0.0001028905,0.878324,0.00002006198,0.00008015631,3.060484e-7,0.002297791,0.000001194074,0.0006333014,0.06155384,0.00009642981,0.05685969],"study_design_scores_gemma":[0.0002449593,0.00005995355,0.9946355,0.00001959546,0.00006947599,0.000001327522,0.0002997457,0.0001334388,0.0003550276,0.002691221,0.001341816,0.0001478978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784092,0.0001240582,0.002329875,0.0009676288,0.0001713373,0.0005587513,0.00002471091,0.00009534558,0.01731912],"genre_scores_gemma":[0.9989488,0.00003037346,0.0001301795,0.0001854699,0.0005825008,0.00004837314,0.0000327277,0.00001273515,0.00002887249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1163115,"threshold_uncertainty_score":0.9993539,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2081618495","doi":"10.1016/j.apgeog.2011.06.017","title":"Critical distances: Comparing measures of spatial accessibility in the riverine landscapes of Peruvian Amazonia","year":2011,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":68,"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":"Amazon rainforest; Geography; Cartography; Physical geography; Ecology; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.04602243554179358,"gpt":0.2912223992105697,"spread":0.2451999636687762,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009955596,0.0001070613,0.0002829009,0.00008933608,0.0001430865,0.00002089963,0.0005959356,0.00006920723,0.0001534272],"category_scores_gemma":[0.0000396578,0.00007744195,0.000125357,0.0004034747,0.0009666804,0.0001403249,0.00002650158,0.0001416658,9.358819e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007330925,"about_ca_system_score_gemma":0.00003884713,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01409551,"about_ca_topic_score_gemma":0.05249114,"domain_scores_codex":[0.9985802,0.000106092,0.0003838645,0.0002455177,0.0004304165,0.0002539074],"domain_scores_gemma":[0.999321,0.0001463854,0.000109934,0.0002832316,0.00008633068,0.00005306063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009946549,0.0002850781,0.9764466,0.00005275337,0.0000119568,9.224194e-7,0.01338072,4.559955e-7,0.00007340308,0.007727385,0.000003057413,0.00191816],"study_design_scores_gemma":[0.0002298168,0.00002032379,0.9835326,0.0000156476,0.00002505483,2.241428e-8,0.002840772,0.000004706895,0.0005357582,0.01254844,0.0001582952,0.0000885801],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9542139,0.0001375179,0.0003802554,0.00003816605,0.00005782859,0.0002513515,0.00001267821,0.00002154777,0.04488682],"genre_scores_gemma":[0.9996395,0.00001621946,0.0002507978,0.00001796447,0.00004292805,0.00002305259,0.000004349709,0.000004183979,0.000001020176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04542565,"threshold_uncertainty_score":0.9924697,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3024728639","doi":"10.1016/j.apgeog.2020.102363","title":"A country comparison of place-based activity response to COVID-19 policies","year":2020,"lang":"en","type":"article","venue":"Applied Geography","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":66,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Business, Innovation and Employment","keywords":"Government (linguistics); Coronavirus disease 2019 (COVID-19); Pandemic; Action (physics); Geography; Work (physics); Public policy; Economic growth; Political science; Disease; Economics; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.2060968290208952,"gpt":0.4331307710275337,"spread":0.2270339420066385,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001073021,0.0002864109,0.0008875658,0.0001821861,0.0001915907,0.00001742029,0.0003683579,0.0001434832,0.00007040269],"category_scores_gemma":[0.006802597,0.0002438981,0.0002136943,0.001158131,0.0002864969,0.00002268558,0.000240602,0.000245705,0.00002794675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000077294,"about_ca_system_score_gemma":0.000126621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003500945,"about_ca_topic_score_gemma":0.00008054818,"domain_scores_codex":[0.9979359,0.0002725128,0.0004979387,0.000473542,0.0004002278,0.0004199078],"domain_scores_gemma":[0.9889503,0.009836922,0.0002906328,0.0004190526,0.0000546159,0.0004485025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.04346111,0.002432646,0.5887258,0.002842566,0.0009159918,0.00001972663,0.01477084,0.01021869,0.05816231,0.06948302,0.2062688,0.002698446],"study_design_scores_gemma":[0.007927995,0.003032324,0.3569281,0.0001157715,0.0005748186,0.000001365332,0.004081157,0.002925008,0.02192673,0.06491326,0.5350626,0.002510866],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.945453,0.00009236795,0.02587541,0.02615381,0.00003197583,0.0009788303,0.0001360826,0.0003887368,0.0008898124],"genre_scores_gemma":[0.9752373,0.000004392041,0.004743873,0.0197823,0.00004800554,0.0001540201,0.000004383538,0.00002153465,0.000004249699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3287937,"threshold_uncertainty_score":0.9945877,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2521254875","doi":"10.1016/j.apgeog.2016.09.013","title":"Water security and rainwater harvesting: A conceptual framework and candidate indicators","year":2016,"lang":"en","type":"article","venue":"Applied Geography","topic":"Water resources management and optimization","field":"Engineering","cited_by":64,"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":"National Science Foundation","keywords":"Rainwater harvesting; Livelihood; Context (archaeology); Water security; Water resource management; Environmental resource management; Environmental planning; Business; Environmental science; Engineering; Geography; Agriculture; Water resources; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.003243402339088419,"gpt":0.1639016759000785,"spread":0.1606582735609901,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008110246,0.0001406849,0.0001142178,0.0001910745,0.00006899423,0.00006528632,0.00006494547,0.00007728178,0.00005447797],"category_scores_gemma":[0.000002175313,0.00008486157,0.00001992074,0.0001085547,0.0001694446,0.00008947132,0.00007107874,0.00007425855,0.00001312165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000042743,"about_ca_system_score_gemma":6.066756e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007944946,"about_ca_topic_score_gemma":0.000002743999,"domain_scores_codex":[0.9993538,0.00000834101,0.0001161196,0.0001885888,0.00008227161,0.0002508369],"domain_scores_gemma":[0.9997564,0.00002306242,0.00001462215,0.000118021,0.000005126756,0.00008278155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002311519,0.0001152118,0.7439962,0.000682348,0.001353913,0.00004035674,0.05214232,0.001718602,0.01507092,0.04526914,0.00415727,0.1352226],"study_design_scores_gemma":[0.0107893,0.0003408844,0.1232147,0.0005190131,0.0005784201,0.00001997281,0.002177386,0.003802668,0.119479,0.100323,0.6336699,0.005085769],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908862,0.0001102958,0.004740503,0.0001020506,0.00005117889,0.0001852384,0.000005852412,0.0002341206,0.003684545],"genre_scores_gemma":[0.9990667,0.0000955811,0.0006050878,0.00008420044,0.00004704965,0.00002938887,0.00001224152,0.00002182518,0.00003800047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6295127,"threshold_uncertainty_score":0.3460554,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2213113255","doi":"10.1016/j.apgeog.2015.12.002","title":"The role of socio-economic status and spatial effects on fresh food access: Two case studies in Canada","year":2015,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":52,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Alberta","funders":"Public Health Agency of Canada","keywords":"Geography; Economies of agglomeration; Inequality; Population; Socioeconomics; Economic geography; Regression analysis; Regional science; Demographic economics; Economic growth; Agricultural economics; Demography; Sociology; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.01859723340879785,"gpt":0.2881652513143497,"spread":0.2695680179055518,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003949239,0.00009897723,0.0001861029,0.00005164255,0.0002596873,0.00003815772,0.0001751412,0.00003135329,0.000004289583],"category_scores_gemma":[0.00001979237,0.0000752991,0.00003390503,0.0001493224,0.0003712999,0.0000756002,0.00003994989,0.00009801883,5.696028e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001393789,"about_ca_system_score_gemma":0.0004935042,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9630758,"about_ca_topic_score_gemma":0.9979904,"domain_scores_codex":[0.9990798,0.00005930176,0.0001854505,0.0001993038,0.000180899,0.0002952876],"domain_scores_gemma":[0.999258,0.0003632203,0.00009241811,0.0001413636,0.0000295237,0.0001154993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004272169,0.00001476128,0.9765276,0.00001163116,0.00004828617,0.00001124601,0.002992401,0.00001241668,0.000002488708,0.001272732,0.00008449996,0.01897927],"study_design_scores_gemma":[0.002549332,0.0001743284,0.8189023,0.00002899839,0.00007705046,7.372648e-7,0.07607019,0.00001904519,0.001343605,0.09521523,0.005182336,0.0004368855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994002,0.001748973,8.184094e-7,0.00007176078,0.0001879517,0.0003308415,0.00002243215,0.00001116266,0.003624092],"genre_scores_gemma":[0.9996932,0.0001145133,0.000006972262,0.00004918971,0.00008115656,0.00004583106,0.000002232345,0.000005093444,0.00000186189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1576253,"threshold_uncertainty_score":0.3070608,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2024893731","doi":"10.1016/j.apgeog.2003.08.005","title":"Gully retreat in a semi-urban catchment in Saskatoon, Saskatchewan","year":2003,"lang":"en","type":"article","venue":"Applied Geography","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":50,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Storm; Surface runoff; Hydrology (agriculture); Drainage; Drainage basin; Precipitation; Erosion; Snowmelt; Geology; Geography; Environmental science; Geomorphology; Ecology; Cartography; Geotechnical engineering; Oceanography; Meteorology","retraction":null,"screen_n_in":null,"score":{"opus":0.006966720821908074,"gpt":0.1807303795040253,"spread":0.1737636586821173,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002866128,0.0001901387,0.0002250934,0.00006602021,0.00006371515,0.00002730617,0.0001705457,0.0001299202,0.000343796],"category_scores_gemma":[0.000002318217,0.00008457264,0.0001076009,0.00113001,0.00005950774,0.00004613486,0.00001378937,0.0001736273,0.00003409608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002399427,"about_ca_system_score_gemma":0.00001064091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029584,"about_ca_topic_score_gemma":0.01731055,"domain_scores_codex":[0.9985877,0.00004044317,0.0003062773,0.0004117354,0.000237069,0.0004168071],"domain_scores_gemma":[0.9996868,0.00005345418,0.00004537111,0.00008910774,0.00001290882,0.0001123293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003490035,0.0002922493,0.9741561,0.000004436257,0.000006086777,0.00001278818,0.0004690164,0.000005316969,0.01860165,0.0006344881,0.0007477623,0.0050352],"study_design_scores_gemma":[0.000606847,0.00009742921,0.9684102,0.00002015334,0.000006118329,0.0000013006,0.002162602,0.000001709296,0.003879878,0.0009639175,0.02357824,0.0002716265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793442,0.0001628791,8.415604e-7,0.0002575249,0.00006325128,0.0003171134,0.00000770627,0.00005899283,0.01978751],"genre_scores_gemma":[0.9989414,0.00002882322,0.00005635148,0.0006154362,0.00002707542,0.00008921175,0.00006039374,0.000001448679,0.000179872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02283048,"threshold_uncertainty_score":0.9659694,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W980076860","doi":"10.1016/j.apgeog.2015.07.012","title":"Extracting ecological information from oblique angle terrestrial landscape photographs: Performance evaluation of the WSL Monoplotting Tool","year":2015,"lang":"en","type":"article","venue":"Applied Geography","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; Graduate Student Association, University at Buffalo","keywords":"Oblique case; Georeference; Geography; Aerial photography; Remote sensing; Photography; Aerial survey; Cartography; Physical geography","retraction":null,"screen_n_in":null,"score":{"opus":0.0153219512523404,"gpt":0.2106862321196989,"spread":0.1953642808673585,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000966328,0.000137703,0.0001332105,0.00005151454,0.0001368961,0.00005151613,0.000247363,0.0001354233,0.0001004674],"category_scores_gemma":[0.0001176767,0.00008729671,0.00009339977,0.0006149288,0.0001087214,0.0003693309,0.0001315948,0.0002031742,0.00004983911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005154355,"about_ca_system_score_gemma":0.00002003934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002876905,"about_ca_topic_score_gemma":0.00005143607,"domain_scores_codex":[0.9984073,0.00009259178,0.000328082,0.0001870132,0.0007835767,0.0002014333],"domain_scores_gemma":[0.9992505,0.00007665862,0.0003201653,0.0002647835,0.00003484379,0.00005299909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001293751,0.0001568962,0.7497665,0.000006117129,0.00005044582,2.993049e-7,0.002643551,0.03223203,0.0159179,0.00001854671,0.002484637,0.1965937],"study_design_scores_gemma":[0.001003388,0.00004765935,0.969413,0.00001688906,0.00006207512,0.000002217624,0.0007483621,0.02032196,0.005987339,0.0008261637,0.001386478,0.0001845116],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753265,0.00001407618,0.00006906327,0.00003883528,0.0002417212,0.0005770315,0.000004117954,0.00004988686,0.02367877],"genre_scores_gemma":[0.9976748,0.000005383112,0.002076412,0.0001065792,0.00007718586,0.00001673083,0.00003583939,0.000005405534,0.000001650048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2196465,"threshold_uncertainty_score":0.3559856,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2912007452","doi":"10.1016/j.apgeog.2019.01.002","title":"Spatial associations between household and community livelihood capitals in rural territories: An example from the Mahanadi Delta, India","year":2019,"lang":"en","type":"article","venue":"Applied Geography","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Economic and Social Research Council; University of Southampton; International Development Research Centre; Department for International Development; Department for International Development, UK Government; Government of the United Kingdom","keywords":"Livelihood; Geography; Natural resource; Social capital; Scale (ratio); Natural capital; Citizen journalism; Census; Natural resource management; Economic growth; Business; Socioeconomics; Economics; Agriculture; Population; Political science; Ecology; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.0151984947048242,"gpt":0.1949449714590628,"spread":0.1797464767542386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003938666,0.0001311665,0.0001924011,0.00003641031,0.0003332758,0.00008829233,0.0003605233,0.00009845656,0.0001664386],"category_scores_gemma":[0.000001994049,0.00009741326,0.00003522294,0.0002066767,0.00003305182,0.0001958159,0.0001848575,0.00026701,0.00005662568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003020566,"about_ca_system_score_gemma":0.000004577868,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6855465,"about_ca_topic_score_gemma":0.3119194,"domain_scores_codex":[0.9990526,0.0001291161,0.0001979329,0.0001847886,0.0001824585,0.0002530721],"domain_scores_gemma":[0.9991546,0.0002896858,0.0000920728,0.0003753279,0.000002942778,0.00008542438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004177093,0.00004194988,0.9943554,0.000002598729,0.00002357086,2.234003e-7,0.00452684,0.00001496381,0.00005762591,0.00001602908,0.00002701796,0.0009296521],"study_design_scores_gemma":[0.0004360401,0.00004236333,0.9944069,0.000009581931,0.00002096341,1.184161e-7,0.003036324,0.00002324174,0.00005609656,0.001493849,0.0003292224,0.0001453312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983098,0.0000320748,0.000005109007,0.00003592253,0.00006728346,0.0003330708,0.0003511851,0.00003287596,0.0008326643],"genre_scores_gemma":[0.9991808,0.00001524314,0.0000489047,0.0001940982,0.00009306875,0.00003079051,0.0004244561,0.00001158991,0.000001033686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3736271,"threshold_uncertainty_score":0.7006363,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4319300878","doi":"10.1016/j.apgeog.2023.102888","title":"New spaces of inequality with the rise of remote work: Autonomy, technostress, and life disruption","year":2023,"lang":"en","type":"article","venue":"Applied Geography","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":39,"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":"Autonomy; Inequality; Work (physics); Flexibility (engineering); Geography; Sociology; Telecommuting; Space (punctuation); Technostress; Economic growth; Economic geography; Political science; Psychology; Engineering; Economics; Computer science; Management; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01195975003331127,"gpt":0.2434395483275721,"spread":0.2314797982942608,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003988394,0.00006190025,0.0001135668,0.00009474027,0.0001304551,0.00003945912,0.0001137042,0.00004960207,0.000009656602],"category_scores_gemma":[0.00000855451,0.00004405819,0.00003739265,0.001008109,0.0003558436,0.0001543924,0.00001849984,0.00005380619,0.000003791004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004087317,"about_ca_system_score_gemma":0.00006524192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007625244,"about_ca_topic_score_gemma":0.0003373181,"domain_scores_codex":[0.9994614,0.0000167282,0.0001511342,0.00009837829,0.0001423617,0.0001299859],"domain_scores_gemma":[0.9996173,0.00007297936,0.0001198679,0.0001137434,0.00002190375,0.00005423019],"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":[0.0001445935,0.00003358076,0.08712985,0.00007061646,0.0000857596,2.496134e-7,0.01414788,0.00009396064,0.00001688624,0.1384819,0.0008112714,0.7589834],"study_design_scores_gemma":[0.001729378,0.0001989047,0.6345369,0.0002393491,0.000160131,2.425366e-7,0.04344987,0.00007493427,0.00152353,0.0728624,0.2445828,0.0006416367],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9514888,0.0001596955,0.001871141,0.002738001,0.00002492899,0.0003770087,0.000009843125,0.0001016845,0.0432289],"genre_scores_gemma":[0.9993781,0.0001136525,0.0004128436,0.00002116769,0.00002112314,0.000005817909,0.000005996086,0.000003386179,0.00003784198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7583418,"threshold_uncertainty_score":0.1796641,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2296068557","doi":"10.1016/j.apgeog.2017.02.009","title":"Population pressure and global markets drive a decade of forest cover change in Africa's Albertine Rift","year":2017,"lang":"en","type":"article","venue":"Applied Geography","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":39,"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":"Deforestation (computer science); Population growth; Geography; Population; Biodiversity; Reforestation; Land cover; Agroforestry; Physical geography; Ecology; Land use; Forestry; Environmental science; Demography; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01018210183330241,"gpt":0.2062501673092166,"spread":0.1960680654759142,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001262953,0.0000885608,0.0001072846,0.00004370531,0.0001689846,0.00002895212,0.0001897436,0.00005380142,0.0001220067],"category_scores_gemma":[0.000008168857,0.00008284253,0.00003451845,0.0001227295,0.0001684613,0.00009511107,0.0003573193,0.00003737406,0.00001133177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001092416,"about_ca_system_score_gemma":8.18705e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006284558,"about_ca_topic_score_gemma":0.002597206,"domain_scores_codex":[0.999332,0.00001248444,0.0001089205,0.0002168297,0.0001746161,0.0001552138],"domain_scores_gemma":[0.9995713,0.00001271111,0.000126529,0.0002414469,0.000003970909,0.00004403028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004347504,0.00004298827,0.9945775,0.00001489045,0.00001824181,9.877155e-7,0.0002832022,0.00004015739,0.00001872073,0.0001061993,0.000144685,0.004708916],"study_design_scores_gemma":[0.0004582498,0.00001304164,0.9872862,0.00000818386,0.00003791527,2.069624e-7,0.00003681433,0.0002088539,0.000006409845,0.0006342187,0.01121959,0.00009036835],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778906,0.00009019405,0.00001371721,0.0002745255,0.00002426084,0.0003551777,0.00001555108,0.000009086277,0.02132693],"genre_scores_gemma":[0.9996402,0.00003497039,0.0001443798,0.00007606584,0.00001245941,0.00001836822,0.00001025481,0.000002659415,0.00006061223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02174967,"threshold_uncertainty_score":0.9500413,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2068789480","doi":"10.1016/j.apgeog.2010.11.020","title":"Mapping spatial variation in food consumption","year":2010,"lang":"en","type":"article","venue":"Applied Geography","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Michael Smith Health Research BC; Public Health Agency of Canada","keywords":"Consumption (sociology); Geography; Spatial variability; Food consumption; Variation (astronomy); Population; Demography; Agricultural economics; Economics; Statistics; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.01084472167771934,"gpt":0.233591681214757,"spread":0.2227469595370377,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001548859,0.0001281007,0.0002123726,0.0002936622,0.00004715003,0.00001727435,0.00006409491,0.0001276424,0.0001068888],"category_scores_gemma":[0.00001688328,0.0001292416,0.00008408055,0.0003467656,0.00007098074,0.00006021433,0.00004196289,0.0004245546,0.0001074251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001303295,"about_ca_system_score_gemma":0.00001564195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001465307,"about_ca_topic_score_gemma":0.0002836007,"domain_scores_codex":[0.9990896,0.00001375715,0.000173298,0.0002761628,0.0002211069,0.0002260818],"domain_scores_gemma":[0.9994947,0.00006384546,0.00006807259,0.0002532338,0.00003242156,0.00008776772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005292636,0.002700953,0.8735012,0.00008753255,0.0000610936,0.000003466776,0.0001987802,0.000002339167,0.09891731,0.01431231,0.00002976857,0.01013226],"study_design_scores_gemma":[0.001173838,0.00008804646,0.9871026,0.00001324446,0.00002003936,0.000002384859,0.0000134765,0.0001082815,0.003248422,0.007553424,0.0005488133,0.0001274664],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934242,0.000007758601,0.0005258622,0.0001442798,0.0001912893,0.0004501557,0.000004949569,0.0000947911,0.005156694],"genre_scores_gemma":[0.9986094,0.000004914769,0.0008301262,0.0001772842,0.0002655936,0.00006254757,0.00003046659,0.00001554291,0.000004166444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1136013,"threshold_uncertainty_score":0.5270319,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200237092","doi":"10.1016/j.apgeog.2021.102625","title":"Analysis of 200 years of change in ontario wetland systems","year":2021,"lang":"en","type":"article","venue":"Applied Geography","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":37,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Wetland; Geography; Population; Agriculture; Period (music); Physical geography; Environmental science; Hydrology (agriculture); Ecology; Archaeology; Geology; Demography","retraction":null,"screen_n_in":null,"score":{"opus":0.03056434026537434,"gpt":0.2072984915513006,"spread":0.1767341512859262,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009270499,0.00005381221,0.0002369642,0.00006215006,0.0000115671,0.000005312949,0.00007722465,0.00005322901,0.0003779174],"category_scores_gemma":[7.920052e-7,0.00002534323,0.0001421314,0.001362571,0.00002658841,0.00001600816,0.00001146921,0.00004892756,0.000001508962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004486696,"about_ca_system_score_gemma":0.000004787717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07519617,"about_ca_topic_score_gemma":0.2835445,"domain_scores_codex":[0.9993917,0.00001178487,0.0001936527,0.0001450051,0.0001540572,0.0001037788],"domain_scores_gemma":[0.999799,0.00003686417,0.00005752275,0.00004873506,0.0000259483,0.00003189609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001217114,0.00008479059,0.9803764,0.000003858739,0.0000845275,0.000002618789,0.000159601,0.00001452013,0.01665195,0.0001928613,0.000007857736,0.002408884],"study_design_scores_gemma":[0.0001082631,0.00002082835,0.9974728,0.000008325572,0.00008598201,1.089361e-7,0.0001871727,0.000009834377,0.0004719364,0.00001231286,0.001568753,0.00005369381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982349,0.000183999,3.815869e-7,0.00002175721,0.00004020658,0.00008501043,0.00002015488,0.000007157306,0.001406456],"genre_scores_gemma":[0.9996942,0.0000488013,0.000008586328,0.00005036249,0.00001071655,0.00001549638,0.000148816,2.824724e-7,0.00002277827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2083483,"threshold_uncertainty_score":0.9309622,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2081963537","doi":"10.1016/j.apgeog.2012.07.005","title":"Identifying, mapping and modelling trajectories of poverty at the neighbourhood level: The case of Montréal, 1986–2006","year":2012,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec; Institut National de la Recherche Scientifique","funders":"","keywords":"Neighbourhood (mathematics); Geography; Census; Multinomial logistic regression; Metropolitan area; Poverty; Gentrification; Immigration; Unemployment; Demography; Demographic economics; Economic geography; Socioeconomics; Sociology; Economic growth; Statistics; Population; Mathematics; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.04828039094731202,"gpt":0.2658525344118086,"spread":0.2175721434644966,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007913291,0.0001424272,0.0002337236,0.00009337732,0.001255429,0.00003957671,0.0001756048,0.00007297864,0.00005401457],"category_scores_gemma":[0.00002599695,0.00008640977,0.0001323533,0.0005608146,0.0007347622,0.0001454693,0.00009908582,0.0001112323,0.00000264573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001410444,"about_ca_system_score_gemma":0.00002011961,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02139696,"about_ca_topic_score_gemma":0.006300612,"domain_scores_codex":[0.9987825,0.00009293525,0.0003034076,0.0001662614,0.0003100797,0.0003447759],"domain_scores_gemma":[0.9988989,0.0004633289,0.0002406925,0.0002344075,0.00009490859,0.00006775522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009326849,0.0002671531,0.3481404,0.0001437942,0.000889898,0.000006871829,0.3286107,0.0004251828,0.0007520892,0.2961467,0.008595832,0.0159281],"study_design_scores_gemma":[0.002613281,0.0001103029,0.2901595,0.0001283675,0.001014113,0.00006199447,0.5414202,0.0009668815,0.00375727,0.04993466,0.1083048,0.001528571],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327511,0.02267059,0.006687568,0.0007387885,0.0003441228,0.0006593321,0.00008774477,0.00005778194,0.03600303],"genre_scores_gemma":[0.99832,0.0009368331,0.0002420716,0.0001249115,0.0001474426,0.0000306861,0.000002540602,0.0000105881,0.0001849399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.246212,"threshold_uncertainty_score":0.9851196,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008305079","doi":"10.1016/j.apgeog.2013.11.003","title":"Mosquitoes &amp; vulnerable spaces: Mapping local knowledge of sites for dengue control in Seremban and Putrajaya Malaysia","year":2013,"lang":"en","type":"article","venue":"Applied Geography","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo; McMaster University; United Nations University Institute for Water, Environment, and Health","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Dengue fever; Geography; Public health; Vector (molecular biology); Socioeconomics; Environmental planning; Cartography; Medicine; Biology; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.00951808437661261,"gpt":0.2382922778056088,"spread":0.2287741934289962,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002561604,0.0002505294,0.0006020127,0.0003316926,0.00008092982,0.00004382813,0.0001144748,0.000137166,0.0001337917],"category_scores_gemma":[0.00003339253,0.0002170504,0.0001812362,0.000448185,0.0001634719,0.00007521978,0.00003529414,0.0001783933,0.00001983262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001411768,"about_ca_system_score_gemma":0.00004620917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002653762,"about_ca_topic_score_gemma":0.0001131573,"domain_scores_codex":[0.9985539,0.00003270619,0.0003977106,0.0004175486,0.0001340784,0.0004640487],"domain_scores_gemma":[0.9989157,0.0002358727,0.0001145799,0.000339445,0.0001741655,0.0002202008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001307342,0.001740882,0.7385249,0.003183985,0.001112553,0.000008326034,0.001808797,0.0005156784,0.1432871,0.01244236,0.007165052,0.08890305],"study_design_scores_gemma":[0.03361351,0.000619925,0.8800786,0.0006113532,0.001057171,0.0000201692,0.006218667,0.0327912,0.002664826,0.009415323,0.0316635,0.001245803],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842814,0.00421349,0.00686178,0.0003734534,0.00005003985,0.002185773,0.00003704502,0.00005652435,0.001940488],"genre_scores_gemma":[0.9972062,0.00006972844,0.001152391,0.0004117927,0.0001318483,0.0008375071,0.00006196452,0.0000321244,0.00009640917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1415537,"threshold_uncertainty_score":0.8851057,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4383222217","doi":"10.1016/j.apgeog.2023.103026","title":"Measuring access to health facilities in Ghana: Implications for implementation of health interventions and the Sustainable Development Goal 3","year":2023,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Socioeconomic status; Health care; Business; Psychological intervention; Sustainable development; Population; Universal design; Geography; Mode of transport; Environmental health; Economic growth; Socioeconomics; Medicine; Transport engineering; Nursing; Political science; Computer science; Engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.08431849482119286,"gpt":0.3873672259562443,"spread":0.3030487311350514,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002667485,0.00006356354,0.0001850844,0.0002689262,0.000767328,0.00006502074,0.0002038331,0.00001848878,0.00001088028],"category_scores_gemma":[0.00001442992,0.00005466075,0.00006948855,0.001042904,0.0001417916,0.0001258462,0.00005278568,0.00004076459,5.660284e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006874719,"about_ca_system_score_gemma":0.0002893608,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01960522,"about_ca_topic_score_gemma":0.06309861,"domain_scores_codex":[0.998829,0.0000640066,0.000439648,0.000185766,0.0001267245,0.0003548738],"domain_scores_gemma":[0.9995323,0.0000979716,0.0001319876,0.0001066785,0.00006686655,0.00006420282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003617169,0.00004911313,0.7762123,0.0007432586,0.00003587878,3.784765e-8,0.06677452,0.00001076533,0.000002198555,0.08613896,0.0004842187,0.06951262],"study_design_scores_gemma":[0.0004655886,0.0000129772,0.9014488,0.00001766734,0.000002880389,5.78354e-9,0.0831722,3.903329e-7,0.000018423,0.01163717,0.003171987,0.00005191355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770754,0.0003200543,0.003965138,0.01502132,0.00003501067,0.003067044,0.00006080675,0.00005971852,0.0003955138],"genre_scores_gemma":[0.9982771,0.00004116806,0.000341062,0.0001599128,0.00001057765,0.001061034,0.00003941742,0.000004065406,0.00006565529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1252365,"threshold_uncertainty_score":0.9869233,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2036536496","doi":"10.1016/j.apgeog.2007.07.012","title":"Spatial patterns and processes of bamboo expansion in Southern China","year":2007,"lang":"en","type":"article","venue":"Applied Geography","topic":"Bamboo properties and applications","field":"Agricultural and Biological Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Roads University","funders":"","keywords":"Bamboo; China; Geography; Production (economics); Factory (object-oriented programming); Distribution (mathematics); Agroforestry; Agricultural economics; Ecology; Environmental science; Economics; Mathematics; Archaeology; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.007234008121536103,"gpt":0.1847779196355027,"spread":0.1775439115139666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001167578,0.00007647835,0.00009951204,0.00001976922,0.00005941546,0.00001166025,0.00008998092,0.00005040196,0.00005449349],"category_scores_gemma":[0.000002557223,0.00002943312,0.00002541605,0.000254278,0.00005249792,0.00002106799,0.00003814197,0.00005529768,0.00000316139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001541278,"about_ca_system_score_gemma":0.000001981853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003417483,"about_ca_topic_score_gemma":0.004736885,"domain_scores_codex":[0.9994304,0.000004637083,0.0001552714,0.0001682638,0.00008801867,0.0001534703],"domain_scores_gemma":[0.9998169,0.00003649871,0.00005193899,0.00003675977,0.00001831603,0.00003960374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004407782,0.0001247278,0.5682727,0.00003179084,0.000005328392,4.716427e-7,0.0004480538,9.666901e-7,0.112996,0.0002810482,0.00000666091,0.3177882],"study_design_scores_gemma":[0.0001018731,0.00005221304,0.9898359,0.00001456335,0.000003708896,5.499614e-7,0.001056582,0.000003015326,0.007539727,0.0007350224,0.0005658194,0.00009099997],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984379,0.0001119981,0.00006010948,0.0001395752,0.000008086741,0.0001770745,0.00002196051,0.00002068476,0.001022619],"genre_scores_gemma":[0.9997432,0.00005313093,0.0000503811,0.00005922132,0.00004517163,0.00002090144,0.00001835242,7.183041e-7,0.000008889057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4215633,"threshold_uncertainty_score":0.5166235,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2195088331","doi":"10.1016/j.apgeog.2015.10.006","title":"Informal recyclers' geographies of surviving neoliberal urbanism in Vancouver, BC","year":2015,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Planning and Governance","field":"Social Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Guelph","funders":"","keywords":"Urbanism; Politics; Geography; Context (archaeology); Neoliberalism (international relations); Economic growth; Rhetorical question; Sociology; Inequality; Political science; Economic geography; Political economy; Architecture","retraction":null,"screen_n_in":null,"score":{"opus":0.01576814905474357,"gpt":0.2419991004802091,"spread":0.2262309514254655,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009133373,0.000143853,0.0002505013,0.0003569954,0.0001290133,0.00003576654,0.0003292378,0.00013646,0.00002159138],"category_scores_gemma":[0.00005946598,0.0001508357,0.0001056999,0.001285923,0.0004087806,0.0002469269,0.00005997979,0.0001960934,0.00001187229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001946865,"about_ca_system_score_gemma":0.0001112952,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03524939,"about_ca_topic_score_gemma":0.02691306,"domain_scores_codex":[0.9983914,0.0000569929,0.0003138634,0.0002106001,0.000550598,0.0004765427],"domain_scores_gemma":[0.9992486,0.0001185176,0.00019254,0.0002038663,0.00007460838,0.0001618199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008794147,0.00008938718,0.9254364,0.00001536038,0.00003686216,0.000004827469,0.02560348,0.0001548381,0.00002046668,0.01996812,0.02400793,0.004574355],"study_design_scores_gemma":[0.002040938,0.0001170479,0.6790243,0.00008934135,0.00003062287,5.751048e-7,0.01571099,0.00003057175,0.0001624924,0.01956378,0.2825486,0.0006806827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7739983,0.0003875207,0.00004315827,0.00007106127,0.0005713225,0.0001967768,0.0000100858,0.00009506175,0.2246268],"genre_scores_gemma":[0.9982967,0.0001002866,0.0006424878,0.0001438122,0.0001075482,0.00002136116,0.000005506325,0.00001083188,0.0006715021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2585407,"threshold_uncertainty_score":0.9908432,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2091297449","doi":"10.1016/j.apgeog.2014.08.002","title":"Urban awareness and attitudes toward conservation: A first look at Canada's cities","year":2014,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"Connaught Fund; Natural Resources Canada; University of Toronto; Ministry of Natural Resources","keywords":"Urbanization; Endangered species; Action (physics); Geography; Biodiversity; Government (linguistics); Environmental planning; Local government; Biodiversity conservation; Political science; Environmental protection; Economic growth; Environmental resource management; Habitat; Public administration; Ecology; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.009771881912603676,"gpt":0.1991693875395971,"spread":0.1893975056269935,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001224233,0.0001433589,0.0001609595,0.000034047,0.0003982638,0.00002733249,0.0001363383,0.00005200242,0.0004531132],"category_scores_gemma":[0.000003238757,0.0001356467,0.00002840328,0.0001787785,0.000274772,0.00005071446,0.0001506826,0.00007156922,0.0000459178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000777493,"about_ca_system_score_gemma":0.0000320958,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5768049,"about_ca_topic_score_gemma":0.9333251,"domain_scores_codex":[0.9989899,0.0000132649,0.0001377256,0.0003056839,0.0002602343,0.000293142],"domain_scores_gemma":[0.9994894,0.00006920125,0.00005963982,0.0002205947,0.000005789016,0.0001553225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001125252,0.00001066167,0.9373571,0.00002834156,0.000009047412,9.171295e-7,0.0001969464,0.000009644763,0.00002490157,0.0007091632,0.06129775,0.0003442953],"study_design_scores_gemma":[0.0002186133,0.00002364971,0.8365114,0.000006356739,0.000009873847,0.000001577159,0.00006579763,0.00003793363,0.00004208319,0.0001998093,0.1627267,0.0001561158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861705,0.0001516641,0.00009510608,0.002232888,0.00006477273,0.0002068296,0.00001187506,0.00004741454,0.01101898],"genre_scores_gemma":[0.996201,0.00004838889,0.0002222442,0.003078103,0.00005213992,0.00004512121,0.00001550841,0.00001130061,0.00032624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3565201,"threshold_uncertainty_score":0.553151,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2588112782","doi":"10.1016/j.apgeog.2017.02.005","title":"Lessons learned from the 2013 Calgary flood: Assessing risk of drinking water well contamination","year":2017,"lang":"en","type":"article","venue":"Applied Geography","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Flood myth; Contamination; Environmental science; Poisson regression; Floodplain; Geography; Hydrology (agriculture); Damages; Water contamination; Water resource management; Environmental health; Ecology; Population; Cartography; Engineering; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.05052219333827958,"gpt":0.3035240364454813,"spread":0.2530018431072018,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005070267,0.0001250516,0.0001594762,0.00003097099,0.0009506355,0.0001330572,0.0003886568,0.00008382041,0.0009185445],"category_scores_gemma":[0.00001399554,0.0000784906,0.00007300103,0.00005341877,0.0002683851,0.000208321,0.0002699646,0.0001910522,0.0002894411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002072625,"about_ca_system_score_gemma":0.000003460882,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052277,"about_ca_topic_score_gemma":0.002036649,"domain_scores_codex":[0.998904,0.00004292526,0.0001934638,0.0002596869,0.0002612333,0.0003387056],"domain_scores_gemma":[0.9989644,0.0001189337,0.0002424107,0.000584053,0.000007788119,0.00008244415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002415363,0.00007064785,0.8644488,0.000009994903,0.00003134854,0.000002011196,0.001861056,0.00004219176,0.01685574,0.0001298228,0.001938656,0.1145855],"study_design_scores_gemma":[0.0004027713,0.00001617656,0.9780363,0.00002479383,0.00005212285,2.801333e-7,0.0002891078,0.0001666476,0.007371493,0.006573892,0.006944568,0.000121843],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757357,0.00005684757,0.0002149742,0.003407991,0.0001215995,0.0002441234,0.00001339219,0.00002421411,0.02018113],"genre_scores_gemma":[0.9985029,0.000614698,0.0003073385,0.0003931635,0.0000759472,0.00002181922,0.00004384897,0.00001359735,0.00002669774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1144637,"threshold_uncertainty_score":0.9999948,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2060584171","doi":"10.1016/j.apgeog.2013.10.003","title":"Examining the economic impact of park facilities on neighboring residential property values","year":2013,"lang":"en","type":"article","venue":"Applied Geography","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Recreation; Property value; Geography; Residential property; Property (philosophy); Economic impact analysis; Urban park; Environmental planning; Environmental resource management; Business; Regional science; Civil engineering; Environmental science; Engineering; Ecology; Real estate; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.06000329181777065,"gpt":0.2068379469982845,"spread":0.1468346551805139,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003420136,0.0001590205,0.000271567,0.0001604145,0.0001244986,0.00006809139,0.0002160512,0.00006294221,0.001867785],"category_scores_gemma":[0.000007257904,0.0001126877,0.0001822098,0.00006317191,0.0001472514,0.0001908989,0.00005826997,0.0001023408,0.001402156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001518401,"about_ca_system_score_gemma":0.0000129323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003875653,"about_ca_topic_score_gemma":0.000009576648,"domain_scores_codex":[0.9989145,0.0000119052,0.0004880047,0.0003196722,0.00002973612,0.0002362165],"domain_scores_gemma":[0.9992341,0.00006877616,0.0002821348,0.0003654441,0.000004362423,0.00004517671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002631944,0.00003736004,0.9596588,0.00001737413,0.0002337705,1.094557e-7,0.001037979,0.01006284,0.00019623,0.02293847,0.001680652,0.00411008],"study_design_scores_gemma":[0.0003254238,0.0001215274,0.9668322,0.000005508596,0.000006658008,3.90163e-7,0.0005190392,0.0008833145,0.0002634632,0.03040416,0.0004512329,0.0001870911],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9417825,0.0001458762,0.00007594965,0.00004682474,0.0001287807,0.0003654769,0.00005574197,0.00002049761,0.0573784],"genre_scores_gemma":[0.999155,0.0001056834,0.0000904768,0.00005008556,0.00008474993,0.0001362289,0.00001587968,0.00001760672,0.0003442153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05737262,"threshold_uncertainty_score":0.9993753,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390870864","doi":"10.1016/j.apgeog.2024.103199","title":"Dynamic equity in urban amenities distribution: An accessibility-driven assessment","year":2024,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":29,"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":"Equity (law); Conceptualization; Geography; Distribution (mathematics); Universal design; Population; Business; Economic growth; Sociology; Economics; Political science; Computer science; Demography; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.021428320160199,"gpt":0.3651361370436381,"spread":0.343707816883439,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008758715,0.0001927703,0.0002390271,0.0001746572,0.0004092535,0.0004969659,0.0005468663,0.000152094,0.0004531899],"category_scores_gemma":[0.000006350419,0.0001849278,0.0001533021,0.001226772,0.0006313187,0.0006507038,0.00008114739,0.0003598896,0.0000159214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002558894,"about_ca_system_score_gemma":0.0002992433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002121675,"about_ca_topic_score_gemma":0.01492363,"domain_scores_codex":[0.9978084,0.0001049469,0.0003675926,0.0006361933,0.0005455518,0.0005373314],"domain_scores_gemma":[0.9992794,0.00009312081,0.00005217826,0.0003589129,0.0000444023,0.0001719239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002174423,0.0002972077,0.9093375,0.0001029539,0.00003443522,0.00001742974,0.003157213,0.000009875664,0.00008060361,0.06509575,0.0002407839,0.02160453],"study_design_scores_gemma":[0.0002007214,0.00003281497,0.9353493,0.0000394231,0.00003735617,8.844547e-8,0.003150887,0.0003471548,0.00001903409,0.04616478,0.01433934,0.0003190927],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9528042,0.0003815356,0.001360346,0.0003885068,0.0003783364,0.0005464725,0.0001526941,0.0004395992,0.04354831],"genre_scores_gemma":[0.9988328,0.00004739497,0.0003122664,0.00008799173,0.0001225172,0.000129755,0.000392338,0.00001329884,0.00006159025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04602865,"threshold_uncertainty_score":0.8327734,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2905131490","doi":"10.1016/j.apgeog.2018.12.002","title":"Spatial and temporal trends of forest cover as a response to policy interventions in the district Chitral, Pakistan","year":2018,"lang":"en","type":"article","venue":"Applied Geography","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Higher Education Commision, Pakistan","keywords":"Deforestation (computer science); Logging; Felling; Geography; Forest degradation; Elevation (ballistics); Illegal logging; Range (aeronautics); Forestry; Environmental science; Agroforestry; Physical geography; Land degradation; Agriculture","retraction":null,"screen_n_in":null,"score":{"opus":0.01053783592603532,"gpt":0.2511930783904875,"spread":0.2406552424644522,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003031978,0.00008134419,0.00007996681,0.000312165,0.0001370404,0.000028171,0.0002030942,0.00002624366,0.0002888739],"category_scores_gemma":[0.000009654946,0.00006130991,0.00007777794,0.001138274,0.0003307406,0.00002657319,0.0001973891,0.00004367347,0.00004434247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000197953,"about_ca_system_score_gemma":0.000004221139,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008126094,"about_ca_topic_score_gemma":0.003773257,"domain_scores_codex":[0.9992986,0.00004653964,0.0001518607,0.0001773,0.0001812592,0.0001444486],"domain_scores_gemma":[0.9996668,0.00003477593,0.00005362293,0.0001935895,0.000004038774,0.00004717596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002749574,0.0001091621,0.9875954,0.000005551414,0.00001133311,0.000001345569,0.001435626,0.000009146685,0.00009834285,0.0002016145,0.0007347376,0.00952282],"study_design_scores_gemma":[0.0003315045,0.0001889733,0.9627289,0.000006303319,0.00001396908,5.586267e-7,0.0004735533,0.000009103434,0.00001857818,0.0002826661,0.03587506,0.00007079237],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827269,0.000007382883,0.0001916377,0.00139767,0.00001533713,0.0001983278,0.00002239177,0.000009460735,0.0154309],"genre_scores_gemma":[0.9991823,0.000003797991,0.00009704993,0.0004619627,0.00002325073,0.00001601249,0.00001052551,0.000002933757,0.0002022028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03514033,"threshold_uncertainty_score":0.9984789,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2925863328","doi":"10.1016/j.apgeog.2019.03.009","title":"What geography can tell us? Effect of higher education on intimate partner violence against women in Uganda","year":2019,"lang":"en","type":"article","venue":"Applied Geography","topic":"Intimate Partner and Family Violence","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Canada Research Chairs; United States Agency for International Development","keywords":"Domestic violence; Socioeconomic status; Geography; Psychological intervention; Vulnerability (computing); Demography; Poison control; Suicide prevention; Psychology; Socioeconomics; Medicine; Environmental health; Population; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.005921537889821048,"gpt":0.2748669353755571,"spread":0.268945397485736,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001070284,0.0002823224,0.0004592162,0.0005994142,0.0001648832,0.000130329,0.0004575486,0.0001897179,0.0002440073],"category_scores_gemma":[0.000009015028,0.0002542903,0.000172919,0.001305563,0.0003824851,0.0002687337,0.00006072111,0.00025717,0.0001748017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008122814,"about_ca_system_score_gemma":0.0001034384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000974334,"about_ca_topic_score_gemma":0.00002796556,"domain_scores_codex":[0.9975902,0.0001583586,0.0003706095,0.0005297246,0.0005245493,0.0008265739],"domain_scores_gemma":[0.9989231,0.0001757799,0.0001886287,0.0004482735,0.00007514168,0.0001890799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002714748,0.000281801,0.9551631,0.0001370162,0.00005049222,0.000001305106,0.002603356,0.0001384862,0.0009550397,0.0142058,0.0001602252,0.02603187],"study_design_scores_gemma":[0.0009962412,0.000326396,0.975648,0.0006123364,0.00002506048,1.415263e-7,0.002312551,0.00001064925,0.003604644,0.004753892,0.01113269,0.0005773641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8507133,0.0002899914,6.079257e-7,0.00002963017,0.001019888,0.0008308069,0.000006027014,0.00006412184,0.1470457],"genre_scores_gemma":[0.9971444,0.001387715,0.00002833882,0.000824478,0.0000972639,0.0003281858,0.00002391063,0.00002321152,0.0001424711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1469032,"threshold_uncertainty_score":0.9999909,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2033516718","doi":"10.1016/j.apgeog.2014.06.001","title":"Spatial quantification and pattern analysis of urban sustainability based on a subjectively weighted indicator model: A case study in the city of Saskatoon, SK, Canada","year":2014,"lang":"en","type":"article","venue":"Applied Geography","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"International Institute for Sustainable Development; University of Saskatchewan","funders":"Social Sciences and Humanities Research Council of Canada; University of Saskatchewan","keywords":"Sustainability; Geography; Spatial analysis; Geomatics; Cartography; Spatialization; Urban planning; Socioeconomic status; Regional science; Environmental resource management; Population; Environmental planning; Remote sensing; Environmental science; Civil engineering; Sociology; Ecology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.005499052698263298,"gpt":0.20320609878561,"spread":0.1977070460873467,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006891746,0.0001076156,0.0002445581,0.000174794,0.00007541419,0.00001074343,0.0001656105,0.00003661383,0.00002376526],"category_scores_gemma":[0.000004762434,0.00007309822,0.00005098435,0.0009248886,0.00004377772,0.0000315057,0.00003610251,0.0000683822,2.2391e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004330457,"about_ca_system_score_gemma":0.00002841184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8275854,"about_ca_topic_score_gemma":0.961055,"domain_scores_codex":[0.9988276,0.0001442495,0.0002783233,0.0003006319,0.0003085396,0.0001406173],"domain_scores_gemma":[0.9992362,0.0001375786,0.0001858811,0.0003849768,0.00001433734,0.00004101547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004042361,0.0003517274,0.994145,0.00002681668,0.00005974611,0.000004612492,0.001420513,0.002945516,0.00001221379,0.000007137576,0.000004498942,0.0009817618],"study_design_scores_gemma":[0.0003304137,0.00008021348,0.8743685,0.000001857799,0.0001628204,3.751346e-7,0.001838559,0.1229907,0.00007906122,0.00006806396,0.000004868119,0.00007448437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980592,0.000002706323,0.001178774,0.00004112609,0.000005656085,0.0005472212,0.00003130725,0.00000506477,0.0001289254],"genre_scores_gemma":[0.9998301,2.905418e-7,0.00001078996,0.00007589151,0.000003195367,0.00006325679,0.0000124744,0.00000390576,1.367844e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1334696,"threshold_uncertainty_score":0.2980859,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2057454049","doi":"10.1016/j.apgeog.2013.06.004","title":"Wild things in urban places: America's largest cities and multi-scales of governance for endangered species conservation","year":2013,"lang":"en","type":"article","venue":"Applied Geography","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Endangered species; Geography; Corporate governance; Nature Conservation; Environmental planning; Environmental resource management; Ecology; Environmental protection; Habitat; Biology; Business; Environmental science","retraction":null,"screen_n_in":null,"score":{"opus":0.007660950231764156,"gpt":0.1857491058144631,"spread":0.1780881555826989,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001127835,0.00009860309,0.0001440206,0.00003780922,0.00007570663,0.00001492762,0.00009928746,0.00006693172,0.0001432997],"category_scores_gemma":[0.00003386014,0.00009619974,0.00003194338,0.0002002427,0.0004366838,0.0002406385,0.00004708786,0.00006211219,0.00001339052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001693711,"about_ca_system_score_gemma":0.000004727793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001387164,"about_ca_topic_score_gemma":0.0006226082,"domain_scores_codex":[0.9993236,0.00001451718,0.0001855971,0.0002018082,0.00009435344,0.0001801051],"domain_scores_gemma":[0.9995428,0.0001639183,0.0001423509,0.0001045668,0.000009213444,0.00003719266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002335415,0.00004793346,0.9898885,0.00001722927,0.000008540879,1.073314e-7,0.0005850829,0.0000149303,0.002127644,0.001210341,0.004740074,0.001336283],"study_design_scores_gemma":[0.0004902676,0.00002989443,0.9919882,0.00001035701,0.000005858799,2.488415e-7,0.0004308574,0.0005592089,0.0003901132,0.001204849,0.004783615,0.0001064992],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964134,0.00009025238,0.0006252079,0.001204192,0.00003022843,0.0004830622,0.00001823851,0.00002115141,0.001114324],"genre_scores_gemma":[0.9910169,0.00009478522,0.006951515,0.00150701,0.0000103263,0.0002507129,0.00001946465,0.000006993815,0.000142289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006326308,"threshold_uncertainty_score":0.3922911,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1968154543","doi":"10.1016/j.apgeog.2014.06.020","title":"Long-term evolution of a sand spit, physical forcing and links to coastal flooding","year":2014,"lang":"en","type":"article","venue":"Applied Geography","topic":"Coastal and Marine Dynamics","field":"Earth and Planetary Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Universidade Nova de Lisboa; Universidade de Lisboa; Llywodraeth Cymru; Federation for the Humanities and Social Sciences","keywords":"Shore; Submarine pipeline; Geology; Coastal geography; Oceanography; Flood myth; Estuary; Beach morphodynamics; Rubble; Longshore drift; Forcing (mathematics); Sediment transport; Fluvial; Flooding (psychology); Beach ridge; Sediment; Hydrology (agriculture); Geography; Archaeology; Climatology; Geomorphology","retraction":null,"screen_n_in":null,"score":{"opus":0.003775398004237505,"gpt":0.1836035593040299,"spread":0.1798281612997924,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001073461,0.0001054044,0.0001566862,0.0001276552,0.00008295631,0.00002608753,0.00008207783,0.00004948685,0.00002154777],"category_scores_gemma":[0.000006169999,0.00009199167,0.00005470733,0.000239836,0.00006788001,0.00005665837,0.00004588303,0.0001111198,0.00001028917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":9.27447e-7,"about_ca_system_score_gemma":0.000006872818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005489,"about_ca_topic_score_gemma":0.001897877,"domain_scores_codex":[0.999332,0.000009697475,0.0001166654,0.0002040297,0.0001348049,0.0002027807],"domain_scores_gemma":[0.9996592,0.00005862276,0.00004340209,0.0001097946,0.00001738682,0.0001115651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004549202,0.00001620067,0.8453772,0.00003576196,0.00001257123,5.430233e-7,0.0001025239,0.0003467303,0.0008063758,0.0009593709,0.000007065371,0.1522901],"study_design_scores_gemma":[0.0002649789,0.0001575316,0.9894726,0.00001499212,0.0000211176,0.000002703765,0.0000302445,0.006590227,0.0002018538,0.003042334,0.00007062953,0.0001307419],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844842,0.00002737251,0.00548269,0.00002545646,0.00006102547,0.0001461768,0.00002778213,0.00002726141,0.009718013],"genre_scores_gemma":[0.9993054,0.000005663475,0.0004784997,0.00004420456,0.00009959214,0.000001677745,0.0000511479,0.000002882881,0.00001092574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1521594,"threshold_uncertainty_score":0.3751311,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2410071568","doi":"10.1016/j.apgeog.2016.05.008","title":"A cost path and network analysis methodology to calculate distances along a complex river network in the Peruvian Amazon","year":2016,"lang":"en","type":"article","venue":"Applied Geography","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; McGill University","funders":"Japan Society for the Promotion of Science; Social Sciences and Humanities Research Council of Canada; University of Toronto","keywords":"Raster graphics; Geography; Amazon rainforest; Fluvial; Network analysis; Geographic information system; Computer science; Destinations; Environmental resource management; Cartography; Environmental science; Ecology; Tourism; Geology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03149389469595901,"gpt":0.269583910688325,"spread":0.238090015992366,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006192194,0.000127786,0.0001998195,0.00009525094,0.0001911846,0.00003689415,0.0001855807,0.0000460906,0.0003399657],"category_scores_gemma":[0.000008349686,0.00007670162,0.00008950373,0.001735,0.0002141938,0.00007908687,0.00008744349,0.00007722244,0.00004894375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002429202,"about_ca_system_score_gemma":0.000002107504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001506043,"about_ca_topic_score_gemma":0.004453233,"domain_scores_codex":[0.9988016,0.0001727697,0.0002068575,0.0003405377,0.0001537176,0.0003245185],"domain_scores_gemma":[0.99927,0.0003202155,0.00007614375,0.0002625168,0.000005595297,0.00006554719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000465355,0.00002129139,0.9671662,8.760355e-7,0.00007467599,0.000002140214,0.0004702185,0.003714732,0.0001423804,0.001291409,0.002189842,0.02487968],"study_design_scores_gemma":[0.0001649392,0.00002356575,0.9632046,0.000006328447,0.0000806461,0.000001341224,0.00013622,0.0004814181,0.000001998106,0.00213645,0.03364072,0.0001217513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619133,0.00004743282,0.0340899,0.001370558,0.0000481106,0.000421223,0.000007980167,0.00002057941,0.00208086],"genre_scores_gemma":[0.9898966,0.00004322,0.007470552,0.0023319,0.0000629314,0.0001581525,0.00001053035,0.000006115642,0.00002001494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03145088,"threshold_uncertainty_score":0.3722387,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2791678370","doi":"10.1016/j.apgeog.2018.01.017","title":"Unequal spatial accessibility of integration-promoting resources and immigrant health: A mixed-methods approach","year":2018,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada; Ryerson University","keywords":"Immigration; Geography; Focus group; Ethnic group; Space (punctuation); Regional science; Focus (optics); Economic geography; Sociology; Computer science; Anthropology","retraction":null,"screen_n_in":null,"score":{"opus":0.01964761376504125,"gpt":0.3384016151306137,"spread":0.3187540013655724,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003668139,0.0001806673,0.0003889846,0.0001744908,0.0007550057,0.00008961663,0.0003699941,0.0001411053,0.0000575876],"category_scores_gemma":[0.00007870046,0.0001555471,0.0001286535,0.000851501,0.001653364,0.0001691364,0.00006326223,0.0001975603,0.000001375387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001963329,"about_ca_system_score_gemma":0.00009686154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02269675,"about_ca_topic_score_gemma":0.008181156,"domain_scores_codex":[0.9976639,0.0003697808,0.0005832196,0.0005765521,0.0003821476,0.0004243793],"domain_scores_gemma":[0.998801,0.0001884272,0.0003514663,0.000332729,0.0001386263,0.0001877664],"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":[0.0001287495,0.000340385,0.4334749,0.000149117,0.0000500698,2.327664e-7,0.06552278,3.652617e-7,0.0008750783,0.004710775,0.00004843184,0.4946991],"study_design_scores_gemma":[0.0005300593,0.0001601444,0.9660115,0.00004066516,0.00003907122,1.185665e-7,0.01380229,0.0001810983,0.002940684,0.01433848,0.001640442,0.0003154067],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564779,0.000329933,0.03215252,0.0001949704,0.0001596118,0.0005570328,0.00001838715,0.0001000596,0.01000962],"genre_scores_gemma":[0.9757313,0.00002165324,0.02381823,0.00008848925,0.0002664147,0.00003606081,0.00001950325,0.00001102107,0.00000740111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5325366,"threshold_uncertainty_score":0.9838112,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1985312935","doi":"10.1016/j.apgeog.2012.02.003","title":"A GIS approach to ecosystem services and rural territorial dynamics applied to the case of the gas industry in Bolivia","year":2012,"lang":"en","type":"article","venue":"Applied Geography","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Environment Research Council; International Development Research Centre","keywords":"Livelihood; Geography; Sustainability; Stakeholder; Ecosystem services; Environmental resource management; Millennium Ecosystem Assessment; Environmental planning; Ecosystem; Environmental change; Environmental protection; Business; Climate change; Ecology; Agriculture; Political science; Environmental science","retraction":null,"screen_n_in":null,"score":{"opus":0.004770543737279033,"gpt":0.1709140730747925,"spread":0.1661435293375135,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003337839,0.0001275081,0.0001226455,0.0000761734,0.000208576,0.00003398868,0.0003418207,0.0001219657,0.00001865576],"category_scores_gemma":[0.000001359726,0.00008149871,0.00004249634,0.0006167943,0.00007561566,0.0000380643,0.0006904277,0.0001857093,0.00001685802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004534591,"about_ca_system_score_gemma":0.000002184714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003763414,"about_ca_topic_score_gemma":0.004719797,"domain_scores_codex":[0.9991617,0.00003209986,0.0001593684,0.0001906488,0.0001938178,0.0002624267],"domain_scores_gemma":[0.9994863,0.0000216041,0.00006532403,0.0003183066,0.000003688782,0.000104817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002973724,0.0001064389,0.9910907,0.00003657086,0.00002117731,8.170632e-7,0.003897034,0.0006274551,0.0001120163,0.0004509334,0.0002618048,0.00336529],"study_design_scores_gemma":[0.0002950724,0.00001164827,0.9784877,0.000008840342,0.000034944,0.000007941235,0.01202702,0.0002913868,0.00003632782,0.00005756095,0.008593692,0.0001479183],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878531,0.00001170293,0.00002905027,0.0004035661,0.0001723698,0.0008379254,0.00002603356,0.0000128979,0.01065341],"genre_scores_gemma":[0.999175,0.0000016764,0.0001688032,0.0004521196,0.0001108015,0.00006691262,0.000005228786,0.000005766159,0.0000137266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01260307,"threshold_uncertainty_score":0.5689181,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3044068434","doi":"10.1016/j.apgeog.2020.102265","title":"Spaces of market politics: Retailscapes and modernist planning imaginaries in African cities","year":2020,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban and Rural Development Challenges","field":"Social Sciences","cited_by":19,"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":"Cityscape; Centrality; Geography; Economic geography; Expropriation; Placemaking; Order (exchange); Politics; Goods and services; Business; Economy; Political science; Economics; Architecture; Urban design; Market economy","retraction":null,"screen_n_in":null,"score":{"opus":0.02320411647338026,"gpt":0.2457637051215364,"spread":0.2225595886481562,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001651548,0.0001015344,0.0001885518,0.0001282231,0.000176653,0.0000621539,0.0001330004,0.0000525009,0.00005931631],"category_scores_gemma":[0.00002122696,0.00009652592,0.0000323579,0.0002592466,0.0007041994,0.00008552249,0.00005255216,0.00009124452,0.000001420738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007591915,"about_ca_system_score_gemma":0.00003865317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005853932,"about_ca_topic_score_gemma":0.0001639725,"domain_scores_codex":[0.9991614,0.00003810632,0.0001511911,0.0001835716,0.000205454,0.0002602989],"domain_scores_gemma":[0.999659,0.0001006816,0.00006145048,0.00005454933,0.00002211742,0.000102214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001077539,0.00004468253,0.4586682,0.000181539,0.00008880766,0.00001107041,0.2446622,0.000008110356,0.0002214984,0.2888668,0.003551032,0.003588439],"study_design_scores_gemma":[0.0007888846,0.00008467468,0.4787682,0.0000968339,0.00003786814,5.559976e-7,0.3474316,0.00007773442,0.0003592062,0.07694319,0.09476911,0.0006421315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5537573,0.0038183,0.00002711651,0.01378106,0.00004640418,0.0002334485,0.00001319548,0.00009140094,0.4282318],"genre_scores_gemma":[0.998518,0.0006289136,0.0004744837,0.0001976447,0.0000541023,0.00001138016,0.000002447338,0.000006622501,0.0001064018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4447607,"threshold_uncertainty_score":0.3936213,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2043444998","doi":"10.1016/j.apgeog.2015.02.002","title":"Temporal stability of model parameters in crime rate analysis: An empirical examination","year":2015,"lang":"en","type":"article","venue":"Applied Geography","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Econometrics; Stability (learning theory); Geography; Statistics; Autocorrelation; Crime rate; Spatial analysis; Order (exchange); Demography; Sociology; Mathematics; Criminology; Computer science; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.1446668640842838,"gpt":0.3932245191198819,"spread":0.2485576550355981,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001919593,0.00007818258,0.0001967883,0.0004121707,0.00006283388,0.00003302772,0.000171639,0.00007043704,0.00006269149],"category_scores_gemma":[0.00003194945,0.00007833677,0.0001755212,0.001247133,0.0002191773,0.0001583512,0.00002545903,0.00008123693,0.000004391611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003460965,"about_ca_system_score_gemma":0.00005089154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007322309,"about_ca_topic_score_gemma":0.008070923,"domain_scores_codex":[0.9987761,0.0002467412,0.0002960409,0.0002379081,0.0002554201,0.0001878219],"domain_scores_gemma":[0.9994141,0.0000416576,0.00009918954,0.0002198211,0.00009920284,0.000125976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002701498,0.0004973607,0.9843665,0.000006551444,0.00007896672,4.068692e-7,0.00921442,0.001551003,0.00008361887,0.002910088,0.0000859858,0.001178119],"study_design_scores_gemma":[0.0004482692,0.00009399516,0.9624165,0.000005285413,0.0001716686,2.516847e-8,0.01359105,0.01182191,0.0004268009,0.01070407,0.0001283603,0.0001921044],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98212,0.0000185101,0.00581949,0.00006972888,0.00002488793,0.0001880669,0.00001437478,0.00002928905,0.01171566],"genre_scores_gemma":[0.9986483,0.000002843043,0.001197375,0.0000477347,0.000009404663,0.00003418862,0.00004592257,0.000004189598,0.00001004926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02195,"threshold_uncertainty_score":0.999288,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160686214","doi":"10.1016/j.apgeog.2021.102460","title":"Visualizing frictional encounters: Analyzing and representing street vendor strategies in Vietnam through narrative mapping","year":2021,"lang":"en","type":"article","venue":"Applied Geography","topic":"Southeast Asian Sociopolitical Studies","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal; McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Narrative; Vendor; Negotiation; Government (linguistics); Livelihood; Space (punctuation); Public relations; Narrative inquiry; Geography; Tourism; Competition (biology); Political science; Sociology; Marketing; Business; Social science; Computer science; Linguistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02372619115709952,"gpt":0.3207590557953706,"spread":0.2970328646382711,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004218496,0.000155243,0.0002627517,0.0001218391,0.0009740817,0.0002231738,0.0001128065,0.00009488612,0.00007079234],"category_scores_gemma":[0.000119039,0.0001708509,0.0001009845,0.001075691,0.0004743663,0.0003007467,0.00009231643,0.0002193132,0.000004864461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005642918,"about_ca_system_score_gemma":0.00009237938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229215,"about_ca_topic_score_gemma":0.001279918,"domain_scores_codex":[0.998237,0.0001516914,0.0002864413,0.0004439157,0.0003624555,0.000518461],"domain_scores_gemma":[0.9993339,0.0002809041,0.00009179508,0.0001219209,0.00009409578,0.00007745439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000007979744,0.00006188409,0.3445387,0.00002751522,0.0001468978,0.00002148166,0.2178035,0.00001024356,0.0002587434,0.4361814,0.0000514984,0.0008902089],"study_design_scores_gemma":[0.0002684777,0.000005923162,0.05375885,0.00005644702,0.00001531513,5.395106e-7,0.8989528,0.000006106207,0.00004776211,0.04483539,0.001866642,0.0001857808],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8432868,0.001640671,0.0008892773,0.0009487417,0.0001611007,0.0002450981,0.000008697422,0.0001196036,0.1527],"genre_scores_gemma":[0.9978392,0.000139647,0.001579528,0.0001209581,0.0002310578,0.00005544037,0.000007608142,0.00001091506,0.00001568588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6811493,"threshold_uncertainty_score":0.7491948,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1981386606","doi":"10.1016/j.apgeog.2014.04.010","title":"Geospatial analysis of oil discharges observed by the National Aerial Surveillance Program in the Canadian Pacific Ocean","year":2014,"lang":"en","type":"article","venue":"Applied Geography","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada; University of Victoria; University of Calgary","funders":"Environment Canada; Canadian Wildlife Federation","keywords":"Geospatial analysis; Recreation; Geography; Oil pollution; Marine pollution; Environmental science; Marine ecosystem; Pollution; Oil spill; Poisson regression; Ecosystem; Environmental resource management; Fishery; Environmental protection; Cartography; Ecology; Environmental health","retraction":null,"screen_n_in":null,"score":{"opus":0.01190384600058,"gpt":0.225079816723004,"spread":0.213175970722424,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001341657,0.0001438856,0.000202045,0.0001310073,0.0002915839,0.00004868378,0.0004508129,0.00006979326,0.0003895022],"category_scores_gemma":[0.00001677866,0.0000877518,0.0001254918,0.001082663,0.0003357186,0.00005260554,0.00003651691,0.0001490013,0.00002249827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008107026,"about_ca_system_score_gemma":0.00002027836,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06170731,"about_ca_topic_score_gemma":0.2682799,"domain_scores_codex":[0.9982875,0.0001269326,0.0002567597,0.000247979,0.0006310583,0.0004497785],"domain_scores_gemma":[0.9993708,0.000127046,0.0001275083,0.0002503413,0.000005122167,0.0001191763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000165655,0.0001110908,0.9925461,0.000002914213,0.00005755016,1.069509e-7,0.0004488585,0.0001797822,0.00009964893,0.000474296,0.001723187,0.004339877],"study_design_scores_gemma":[0.0002304216,0.0000396715,0.9712237,9.179367e-7,0.00003382864,1.243593e-7,0.00009677759,0.0003043039,0.00002286089,0.0002490806,0.02768446,0.0001139066],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723702,0.00002012859,0.000007840383,0.002134036,0.00004290811,0.0002575072,0.00007308311,0.00001455392,0.02507973],"genre_scores_gemma":[0.9990115,0.00002292543,0.00008601602,0.000576846,0.0000491292,0.00005167532,0.0001656785,0.000007861357,0.00002834341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2065726,"threshold_uncertainty_score":0.9445409,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3005730190","doi":"10.1016/j.apgeog.2020.102167","title":"Technology, talent and economic segregation in cities","year":2020,"lang":"en","type":"article","venue":"Applied Geography","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Economic geography; Work (physics); Relation (database); Geography; Regional science; Engineering; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01293954621832674,"gpt":0.1753356132333242,"spread":0.1623960670149974,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001044518,0.0001116935,0.0003011275,0.000469246,0.00004723105,0.00004451803,0.0001206614,0.00008686378,0.0001004474],"category_scores_gemma":[0.000004853189,0.000137641,0.00007585871,0.0002643614,0.0001049196,0.00007607345,0.00005765091,0.00009660114,0.0001776803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000233285,"about_ca_system_score_gemma":0.00000582531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004261307,"about_ca_topic_score_gemma":0.0001395817,"domain_scores_codex":[0.9990845,0.0000020636,0.0003756371,0.000367509,0.00001141897,0.0001589133],"domain_scores_gemma":[0.9996472,0.00001365964,0.0001514702,0.0001213571,0.000004271046,0.00006201768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008635849,0.00000963397,0.2694708,0.000008196632,0.00003784337,6.777146e-7,0.0001042149,0.0003071529,0.00001041049,0.7278394,0.00009804552,0.002105048],"study_design_scores_gemma":[0.001119772,0.00008398645,0.1611955,0.000007020986,0.0000124848,0.000001699088,0.0004490092,0.01467956,0.0001362616,0.7804673,0.04127676,0.0005705537],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731731,0.00121497,0.0003881172,0.009453071,0.00004274777,0.0001489908,0.00004771071,0.00003814691,0.01549316],"genre_scores_gemma":[0.9982085,0.0006607287,0.0003696021,0.0006390206,0.00004097405,0.00004158705,0.00001605744,0.00001085794,0.00001272695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1082752,"threshold_uncertainty_score":0.5612837,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389280069","doi":"10.1016/j.apgeog.2023.103167","title":"The utility of street view imagery in environmental audits for runnability","year":2023,"lang":"en","type":"article","venue":"Applied Geography","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Audit; Proxy (statistics); Metropolitan area; Cartography; Geography; Data science; Computer science; Accounting; Business; Machine learning; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.01482348438163733,"gpt":0.2712937700707065,"spread":0.2564702856890692,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001767072,0.00009405908,0.0001731417,0.00006430982,0.0003764684,0.00002027435,0.0003166882,0.00007053126,0.0000864134],"category_scores_gemma":[0.00003174221,0.00007412989,0.0001710212,0.0006439721,0.0008805289,0.00007699583,0.00003361738,0.0000911451,0.000006554795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001426731,"about_ca_system_score_gemma":0.00004210004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006855503,"about_ca_topic_score_gemma":0.004614858,"domain_scores_codex":[0.99873,0.00005559853,0.0003128579,0.0002827248,0.0002633543,0.0003554389],"domain_scores_gemma":[0.9991888,0.0003591192,0.00008891908,0.0002928912,0.00001332562,0.0000569781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003767786,0.00009492192,0.975477,0.00003013766,0.00001096729,2.87001e-7,0.0006187829,4.210397e-7,0.00008186903,0.0007510309,0.0003618053,0.02253505],"study_design_scores_gemma":[0.0001870837,0.000007947638,0.965075,0.000003725343,0.000009314104,2.754386e-9,0.001479703,0.00000875488,0.0001795893,0.02107138,0.0119008,0.00007671689],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942032,0.0001905364,0.00002768435,0.0002621647,0.0001021461,0.0008088609,0.00009121811,0.00005750591,0.004256751],"genre_scores_gemma":[0.9995002,0.0001583971,0.00004868108,0.00002646794,0.00004097836,0.0001597918,0.0000351332,0.000005639248,0.00002475436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02245834,"threshold_uncertainty_score":0.3244346,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4323657760","doi":"10.1016/j.apgeog.2023.102923","title":"Spatio-temporal heterogeneity in the international trade resilience during COVID-19","year":2023,"lang":"en","type":"article","venue":"Applied Geography","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"National University of Singapore","keywords":"Pandemic; Resilience (materials science); Vulnerability (computing); Mainland China; Coronavirus disease 2019 (COVID-19); Development economics; China; Psychological resilience; Geography; Corporate governance; Business; International trade; Economics; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.1398479301441392,"gpt":0.3927199419247035,"spread":0.2528720117805643,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001561702,0.000177253,0.0002531647,0.0002260933,0.0002677468,0.0000352981,0.0006656292,0.0000798453,0.00003771079],"category_scores_gemma":[0.001248052,0.0001233317,0.0001547275,0.0009984761,0.0001843777,0.00004173179,0.000237295,0.0002250168,0.00003106571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006443557,"about_ca_system_score_gemma":0.00002142342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000198588,"about_ca_topic_score_gemma":0.000709349,"domain_scores_codex":[0.9982744,0.0001154149,0.0004020063,0.0004222451,0.0004131422,0.0003728159],"domain_scores_gemma":[0.9970747,0.002339068,0.0001287989,0.0003680963,0.000006792372,0.00008249283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008793658,0.0001287031,0.9521129,0.0001047707,0.00006704348,0.0000427721,0.001205773,0.0005443884,0.0002108168,0.03637307,0.008715437,0.0004063814],"study_design_scores_gemma":[0.0005496388,0.00001960772,0.8148898,0.000008911335,0.00001293555,0.00000314288,0.0005575141,0.0001425944,0.0001635723,0.1677645,0.01568309,0.0002046382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836198,0.00004188424,0.0004034241,0.01373852,0.0000889481,0.0004826993,0.00002102585,0.0002913837,0.001312313],"genre_scores_gemma":[0.9955972,0.0000726959,0.0006320636,0.003300501,0.00007986386,0.0002753502,0.00002445596,0.00001097079,0.000006837062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1372231,"threshold_uncertainty_score":0.5029319,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2148709437","doi":"10.1016/j.apgeog.2013.11.006","title":"The socio-ecological dimensions of hydrocarbon development in the Disko Bay region of Greenland: Opportunities, risks, and tradeoffs","year":2013,"lang":"en","type":"article","venue":"Applied Geography","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":16,"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":"Livelihood; Bay; Geography; Baseline (sea); Psychological resilience; Government (linguistics); Arctic; Politics; Environmental resource management; Environmental planning; Ecology; Political science; Agriculture; Environmental science","retraction":null,"screen_n_in":null,"score":{"opus":0.0726691759474761,"gpt":0.3063203241380692,"spread":0.2336511481905931,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009207209,0.0001317236,0.0002950395,0.00008596856,0.001995128,0.000003670313,0.0001943345,0.0001722061,0.00002685654],"category_scores_gemma":[0.00002050884,0.00006226957,0.00005529715,0.0001756511,0.000350564,0.00001827051,0.0001645184,0.0003518734,0.000006317934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002555611,"about_ca_system_score_gemma":0.0001016814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00229366,"about_ca_topic_score_gemma":0.004726245,"domain_scores_codex":[0.9983147,0.0002435034,0.0005358817,0.0001678675,0.0001491393,0.000588842],"domain_scores_gemma":[0.9982897,0.001119689,0.000263485,0.0002208385,0.00005935348,0.00004694141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001027156,0.0003964341,0.8711465,0.0001595371,0.000208398,0.000004975392,0.08269212,0.000003321865,0.00006476106,0.02617467,0.007186939,0.01185961],"study_design_scores_gemma":[0.0005635791,0.000124935,0.8892416,0.00002037877,0.00002672826,0.000001327596,0.08505504,0.000007413968,0.000007280758,0.005284285,0.01955648,0.0001109161],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885126,0.0004359049,0.000009050201,0.002035613,0.00008386411,0.001427102,0.000003083911,0.00001307283,0.007479679],"genre_scores_gemma":[0.9964803,0.00199022,0.00007937467,0.0006065281,0.00002781734,0.0007521553,0.000009672784,0.00000818746,0.00004578026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02089038,"threshold_uncertainty_score":0.9993041,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3187450784","doi":"10.1016/j.apgeog.2021.102530","title":"Fenced off: Measuring growing restrictions on resource access for smallholders in the Argentine Chaco","year":2021,"lang":"en","type":"article","venue":"Applied Geography","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":15,"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":"Livelihood; Deforestation (computer science); Geography; Agriculture; Natural resource; Agroforestry; Natural resource economics; Commodity; Frontier; Resource (disambiguation); Ecosystem services; Business; Shifting cultivation; Ecosystem; Environmental protection; Economics; Ecology; Environmental science","retraction":null,"screen_n_in":null,"score":{"opus":0.03554359766693763,"gpt":0.2246484920261013,"spread":0.1891048943591637,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036815,0.0001157722,0.00009351332,0.0001270822,0.0004851115,0.00009867173,0.0004107866,0.00004229319,0.0001080607],"category_scores_gemma":[0.00002042564,0.00009733411,0.0001089715,0.001040982,0.00008441882,0.00008110343,0.0002352184,0.0001138628,0.00002254276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003388388,"about_ca_system_score_gemma":0.000004742249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001922888,"about_ca_topic_score_gemma":0.0001866047,"domain_scores_codex":[0.9988657,0.0000404737,0.0001524992,0.0003566458,0.0003191796,0.0002655504],"domain_scores_gemma":[0.9994836,0.0001076636,0.00005628177,0.0003031904,0.000007911299,0.00004137921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006810494,0.0003256089,0.9743729,0.00002846947,0.00005596647,0.0000130228,0.001174156,0.00623885,0.00154592,0.0009332474,0.002503681,0.01274013],"study_design_scores_gemma":[0.000490942,0.0000159455,0.866166,0.00001045822,0.00002931003,6.095068e-7,0.001864292,0.00009235106,0.0004697567,0.0003947919,0.1303268,0.0001386926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970058,0.00004249567,0.0002847739,0.002259794,0.0000640107,0.000497909,0.000004819919,0.00003837523,0.0267498],"genre_scores_gemma":[0.9969654,0.00004027052,0.0002139504,0.002449471,0.00004097346,0.0001041642,0.00002658622,0.00000740746,0.0001517671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1278231,"threshold_uncertainty_score":0.396917,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401505275","doi":"10.1016/j.apgeog.2024.103372","title":"Ecosystem service demand and supply dynamics under different farming systems: A participatory GIS assessment in Malawi","year":2024,"lang":"en","type":"article","venue":"Applied Geography","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Cornell Atkinson Center for Sustainability, Cornell University; David R. Atkinson Center for a Sustainable Future , Cornell University; McKnight Foundation","keywords":"Ecosystem services; Geography; Citizen journalism; Environmental resource management; Agriculture; Service (business); Ecosystem; System dynamics; Environmental planning; Supply and demand; Participatory GIS; Business; Ecology; Environmental science; Economics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01018860356483415,"gpt":0.2301682476482508,"spread":0.2199796440834167,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003779588,0.0002616685,0.000314208,0.0001449142,0.0001194932,0.000230809,0.0001923004,0.0001155093,0.0001558708],"category_scores_gemma":[4.129063e-7,0.0002031143,0.0000592949,0.0004965477,0.00001541131,0.0001716152,0.0002120833,0.0001863832,0.0001195992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623359,"about_ca_system_score_gemma":0.000009555684,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278119,"about_ca_topic_score_gemma":0.02105543,"domain_scores_codex":[0.9982357,0.00006513234,0.000386385,0.0005557001,0.0003015199,0.0004555442],"domain_scores_gemma":[0.9994211,0.00009033638,0.00006177772,0.0002696355,0.000004776931,0.0001524134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001846692,0.0001236671,0.9830259,0.001479709,0.0001350899,0.00004082439,0.0006433858,0.00751134,0.0004019823,0.005085469,0.00006028525,0.001473881],"study_design_scores_gemma":[0.000653029,0.00005626131,0.6073503,0.0004972572,0.0001292613,0.00002248336,0.002402807,0.3851992,0.00005657214,0.00125242,0.001784117,0.0005962393],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951983,0.0006855795,0.0002882477,0.0002185601,0.0002423252,0.0005305312,0.00004274761,0.0001169767,0.002676744],"genre_scores_gemma":[0.9992913,0.000104145,0.00004980897,0.0001465219,0.00003953175,0.0003018998,0.00003111799,0.00002855666,0.000007146895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3776879,"threshold_uncertainty_score":0.9968078,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}