{"meta":{"query_hash":"ede0f44e50e3","filters":{"venue":"Journal of Spatial Information Science"},"cohort_total":11,"direct_labels_cover":0,"predictions_cover":11,"exported":11,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/ede0f44e50e3","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Spatial+Information+Science"},"results":[{"id":"W2306629633","doi":"10.5311/josis.0.0.75","title":"Visualizing perceived spatial data quality of 3D objects within virtual globes","year":2009,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Memorial University of Newfoundland","funders":"","keywords":"Visualization; Computer science; Metadata; Quality (philosophy); The Internet; World Wide Web; Data visualization; Information retrieval; Data science; Data mining","score_opus":0.07413617483992825,"score_gpt":0.39510422791812344,"score_spread":0.3209680530781952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2306629633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9149771,0.000045196943,0.04282741,0.0011462377,0.0023760023,0.00044881905,0.00004618614,0.00005353077,0.038079545],"genre_scores_gemma":[0.9977416,0.00006214178,0.0016252532,0.0003134059,0.00023446712,7.0841736e-7,0.0000055217783,0.0000019116003,0.00001501602],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99434906,0.00016293499,0.0020973377,0.00011791183,0.0029340964,0.00033866748],"domain_scores_gemma":[0.99353623,0.00016847457,0.0030671076,0.00035810925,0.002680765,0.00018931893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011885399,0.00013757916,0.0003946507,0.00072688743,0.00090506737,0.00035030238,0.0014533573,0.00008402092,0.00003823983],"category_scores_gemma":[0.004182759,0.0001151876,0.00008218151,0.0012491217,0.00096361275,0.01332462,0.00017878872,0.00020780532,0.000020757074],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041910989,0.00024369474,0.026587712,0.00010462078,0.00010108535,0.0000032432297,0.6545057,0.0021528322,0.005466501,0.06470929,0.00081603363,0.24489015],"study_design_scores_gemma":[0.002604178,0.0013118909,0.6764473,0.0005299187,0.00006495988,0.000039366892,0.29660356,0.011574322,0.0016194091,0.00086270657,0.007563695,0.0007787462],"about_ca_topic_score_codex":0.010050037,"about_ca_topic_score_gemma":0.0021270176,"teacher_disagreement_score":0.64985955,"about_ca_system_score_codex":0.00020420532,"about_ca_system_score_gemma":0.0011834677,"threshold_uncertainty_score":0.9965421},"labels":[],"label_agreement":null},{"id":"W3113739508","doi":"10.5311/josis.2020.21.721","title":"Integrated science of movement","year":2020,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Leverhulme Trust","keywords":"Movement (music); Bridge (graph theory); Data science; Focus (optics); Process (computing); Computer science","score_opus":0.031204252940049575,"score_gpt":0.3035085948410572,"score_spread":0.2723043419010076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113739508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76632565,0.000057638666,0.07503091,0.011647717,0.0026373256,0.00068760203,0.000017646451,0.00006153682,0.14353397],"genre_scores_gemma":[0.99795985,0.000040685463,0.0011853216,0.00072425714,0.00008040852,0.0000011410103,2.6415313e-7,0.0000010719992,0.0000070242104],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9959859,0.000025002933,0.0010552012,0.000060000853,0.0026179184,0.00025596848],"domain_scores_gemma":[0.9934352,0.000043428678,0.0014287572,0.000091488524,0.00474709,0.0002540141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005126541,0.000072455536,0.00019350482,0.0007283869,0.0006969241,0.00023669653,0.00090097473,0.0000278255,0.000060510996],"category_scores_gemma":[0.0026145217,0.000056904264,0.00006505409,0.0035486259,0.002393708,0.009365988,0.00010917336,0.00012911958,0.000028350743],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016055809,0.00007906239,0.022269024,0.0001304168,0.000048861453,0.000002083214,0.68570095,0.0027132975,0.017527016,0.160773,0.0018787454,0.10871697],"study_design_scores_gemma":[0.0033469002,0.0019220462,0.10879476,0.00048422415,0.00006563676,0.000020589396,0.5591347,0.022242842,0.07307881,0.0029027157,0.22705549,0.0009512474],"about_ca_topic_score_codex":0.0012599254,"about_ca_topic_score_gemma":0.00004516667,"teacher_disagreement_score":0.23163417,"about_ca_system_score_codex":0.00015307419,"about_ca_system_score_gemma":0.0019630236,"threshold_uncertainty_score":0.8819717},"labels":[],"label_agreement":null},{"id":"W3177093977","doi":"10.5311/josis.2021.22.681","title":"Surface network extraction from high resolution digital terrain models","year":2021,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Terrain; Triangulated irregular network; Computation; Raster graphics; Triangulation; Digital elevation model; Grid; Surface (topology); Computer science; Regular grid; Consistency (knowledge bases); Algorithm; Ridge; Raised-relief map; Topology (electrical circuits); Geology; Artificial intelligence; Remote sensing; Geometry; Geography; Geodesy; Mathematics; Cartography","score_opus":0.013881598999498217,"score_gpt":0.24379144779215273,"score_spread":0.2299098487926545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177093977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5710572,0.000009666044,0.4185272,0.00060139346,0.00035826085,0.000044447857,0.0000071458844,0.000011596153,0.009383107],"genre_scores_gemma":[0.9831664,0.000019208994,0.016459597,0.00016540955,0.00012509017,1.359012e-7,0.000011617046,0.000002499084,0.000050068185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984925,0.000020162788,0.00046360312,0.00009659071,0.0007543326,0.00017283132],"domain_scores_gemma":[0.9990563,0.00004714151,0.00045436132,0.0001710029,0.00015551555,0.00011570922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005729541,0.00006985198,0.000099596946,0.000041408857,0.00027201808,0.00034281024,0.00020477164,0.000040885698,0.0001557934],"category_scores_gemma":[0.0001231505,0.00006197378,0.00004633155,0.00056999834,0.00019712781,0.007324827,0.00008364744,0.00015281625,0.00015076468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000214523,0.000029027358,0.00090526295,0.0000010205189,0.000004189517,0.0000024093952,0.00095992873,0.88553154,0.01234206,0.00019656787,0.0016432554,0.098363295],"study_design_scores_gemma":[0.00054219196,0.000090728296,0.11518398,0.00005615855,0.000019591555,0.00018415108,0.0007835163,0.83202636,0.011087364,0.011027978,0.028725483,0.00027249078],"about_ca_topic_score_codex":0.0008918724,"about_ca_topic_score_gemma":0.00005937721,"teacher_disagreement_score":0.41210917,"about_ca_system_score_codex":0.00021733805,"about_ca_system_score_gemma":0.00011858357,"threshold_uncertainty_score":0.53103226},"labels":[],"label_agreement":null},{"id":"W4205095874","doi":"10.5311/josis.2021.23.155","title":"Deriving topological relations from topologically augmented direction relation matrices","year":2021,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University; National Science Foundation","keywords":"Relation (database); Topological conjugacy; Mathematics; Matrix (chemical analysis); Topology (electrical circuits); Spatial relation; Pure mathematics; Computer science; Geometry; Combinatorics; Data mining","score_opus":0.012821357578306393,"score_gpt":0.2528888854785233,"score_spread":0.2400675279002169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205095874","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.081949405,0.000034013286,0.9108396,0.0023350294,0.0010317919,0.000053307893,0.0000018969972,0.000049449478,0.0037054587],"genre_scores_gemma":[0.9128237,0.00007955462,0.08669128,0.00030674305,0.00006543287,0.0000010998697,0.000004926482,0.0000012024187,0.000026103522],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99829745,0.000067926565,0.0006910301,0.00012533597,0.0006735911,0.00014464896],"domain_scores_gemma":[0.9977759,0.00015197851,0.0007101712,0.00016660648,0.0010845936,0.000110725814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007259635,0.00008102252,0.00013050111,0.000340008,0.00037155693,0.0005014955,0.0003507853,0.00007035007,0.00031686312],"category_scores_gemma":[0.0010736592,0.000068262554,0.00006701273,0.0011150069,0.00012825501,0.008582841,0.000113696115,0.00019398399,0.000041424773],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051838862,0.00016488731,0.05000533,0.000010206338,0.00004573231,0.00003089636,0.00474978,0.05040585,0.020460457,0.07421658,0.00051441684,0.799344],"study_design_scores_gemma":[0.00065972336,0.0001473067,0.6773153,0.000055919652,0.000018214501,0.00023613696,0.00055490126,0.30497664,0.0068505094,0.004624365,0.0043387422,0.0002222183],"about_ca_topic_score_codex":0.00006922774,"about_ca_topic_score_gemma":0.000028423947,"teacher_disagreement_score":0.83087426,"about_ca_system_score_codex":0.00017479964,"about_ca_system_score_gemma":0.0004427182,"threshold_uncertainty_score":0.62223524},"labels":[],"label_agreement":null},{"id":"W4206007840","doi":"10.5311/josis.2021.23.170","title":"Identifying regional variation in place visit behavior during a global pandemic","year":2021,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; Brown University","keywords":"Pandemic; Duration (music); Geography; Psychological resilience; Variation (astronomy); Government (linguistics); Demography; Demographic economics; Coronavirus disease 2019 (COVID-19); Socioeconomics; Economic geography; Psychology; Sociology; Social psychology; Medicine; Economics; Disease","score_opus":0.053831943193666035,"score_gpt":0.3561156446331671,"score_spread":0.30228370143950106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206007840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98209345,0.000092590504,0.012302632,0.0008797527,0.000797992,0.000103788894,0.000003849033,0.000017028357,0.00370891],"genre_scores_gemma":[0.99868906,0.00023403951,0.00068405794,0.00014866874,0.0001757141,0.0000030101442,0.0000010073045,0.0000013715431,0.00006306782],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99760973,0.00007717436,0.00065344875,0.000090724425,0.0013345181,0.00023440982],"domain_scores_gemma":[0.9979859,0.00007509859,0.00060028274,0.00007789861,0.0011476439,0.00011317681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018347322,0.000071511684,0.00015019112,0.00026268186,0.0006366102,0.00036485467,0.00027045567,0.000055093118,0.000078187324],"category_scores_gemma":[0.0009990267,0.00006877905,0.00005955637,0.0012952846,0.00022968423,0.006035655,0.000060387953,0.00014970511,0.000017779063],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014418585,0.00018018202,0.7940789,0.000040886982,0.000030022742,0.000050204468,0.15389004,0.0018600356,0.004714382,0.014413742,0.00035271907,0.030244693],"study_design_scores_gemma":[0.0006833198,0.000022247095,0.9856061,0.00006819244,0.000014167797,0.00006032439,0.010103881,0.000586049,0.0001854346,0.0004616309,0.0020949224,0.00011376504],"about_ca_topic_score_codex":0.0012384092,"about_ca_topic_score_gemma":0.002163245,"teacher_disagreement_score":0.19152717,"about_ca_system_score_codex":0.0006422274,"about_ca_system_score_gemma":0.0013050677,"threshold_uncertainty_score":0.48963556},"labels":[],"label_agreement":null},{"id":"W4288754847","doi":"10.5311/josis.2022.24.199","title":"Temporally relevant parallel top-k spatial keyword search","year":2022,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Computer science; Exploit; Search engine indexing; Information retrieval; Ranking (information retrieval); Data mining; Relevance (law); Visitor pattern","score_opus":0.019932350311511565,"score_gpt":0.26737424443389285,"score_spread":0.2474418941223813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288754847","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012530954,0.000013305216,0.97936904,0.0030522714,0.0015227668,0.00014759574,0.0000071939953,0.00003149829,0.0033253632],"genre_scores_gemma":[0.94691396,0.0000226278,0.051840477,0.0009153922,0.00015651922,0.000005167017,0.0000058784153,0.0000031735615,0.00013680497],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99642193,0.00005705087,0.0007348522,0.00014002692,0.0023307747,0.00031533578],"domain_scores_gemma":[0.9983338,0.00003832217,0.0006251169,0.0003716548,0.0004716416,0.00015942943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036096661,0.000101898615,0.00015686001,0.00076830894,0.00063837203,0.00084937376,0.0029067674,0.000015626701,0.00011406879],"category_scores_gemma":[0.00012657479,0.00008694045,0.00007274622,0.0012390163,0.00013464906,0.012465359,0.0013658969,0.00033363356,0.000057391397],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007539001,0.00011913137,0.0013504368,0.000020122743,0.00001808354,0.000050235365,0.004106441,0.0218302,0.00059718726,0.022255959,0.005295414,0.9442814],"study_design_scores_gemma":[0.0015859364,0.0012611459,0.017464021,0.0000257237,0.0000103605835,0.00025666418,0.0012044206,0.7898218,0.0010945578,0.0015657353,0.18528351,0.0004261121],"about_ca_topic_score_codex":0.0003662277,"about_ca_topic_score_gemma":0.000007969899,"teacher_disagreement_score":0.9438553,"about_ca_system_score_codex":0.00016522087,"about_ca_system_score_gemma":0.00061211473,"threshold_uncertainty_score":0.9037084},"labels":[],"label_agreement":null},{"id":"W4378473062","doi":"10.5311/josis.2023.26.240","title":"Surface network and drainage network: towards a common data structure","year":2023,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Terrain; Drainage; Drainage network; Triangulated irregular network; Digital elevation model; Geology; Computer science; Remote sensing; Geography; Cartography","score_opus":0.02366392206877442,"score_gpt":0.27352856708439016,"score_spread":0.24986464501561573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378473062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97688234,0.00003323047,0.007208041,0.0035900236,0.0009779397,0.00017983082,0.000014348566,0.000036141988,0.01107808],"genre_scores_gemma":[0.99796844,0.00007599252,0.0011813783,0.0006390846,0.00009264478,2.46526e-7,0.000007316625,0.0000018403081,0.00003305443],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987359,0.000026738267,0.00034189684,0.000099026736,0.00050372275,0.00029271643],"domain_scores_gemma":[0.999342,0.00003466007,0.00030434603,0.00021147793,0.000026914498,0.00008060036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002189487,0.00007903106,0.00013700522,0.000059767204,0.0004691025,0.00011137646,0.00065387966,0.000032203858,0.00010349265],"category_scores_gemma":[0.00009162694,0.00005872409,0.000014850924,0.0007453294,0.0005077864,0.0039972486,0.0012587936,0.00014280951,0.00006253349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007202834,0.000010124882,0.10472599,0.000019476021,0.00003035176,0.000016216967,0.0031727573,0.75843555,0.00020360088,0.0006275972,0.05584276,0.07684357],"study_design_scores_gemma":[0.00050878443,0.00017294678,0.7077151,0.000030494879,0.000030541498,0.000043225547,0.0003713625,0.2212175,0.00007669068,0.0072925645,0.062334336,0.00020647715],"about_ca_topic_score_codex":0.00018197812,"about_ca_topic_score_gemma":0.000119242206,"teacher_disagreement_score":0.6029891,"about_ca_system_score_codex":0.00003875972,"about_ca_system_score_gemma":0.00002213978,"threshold_uncertainty_score":0.36080045},"labels":[],"label_agreement":null},{"id":"W4390044434","doi":"10.5311/josis.2023.27.220","title":"Distributed spatial data sharing: a new model for data ownership and access control","year":2023,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Wilfrid Laurier University","funders":"Global Water Futures","keywords":"Geospatial analysis; Computer science; Data sharing; Spatial data infrastructure; The Internet; Data science; Data discovery; World Wide Web; Spatial analysis; Metadata; Geography","score_opus":0.20956805442412918,"score_gpt":0.3778157943723835,"score_spread":0.16824773994825432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390044434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039246045,0.000010174148,0.9826685,0.01229828,0.000441355,0.00027234832,0.00022405201,0.0001331824,0.000027471599],"genre_scores_gemma":[0.9411939,0.00002274915,0.057853326,0.00068343047,0.00013725259,0.0000040115083,0.00008702274,0.000004113508,0.000014221702],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975909,0.000009787527,0.00070442056,0.00033856623,0.00095402077,0.00040231226],"domain_scores_gemma":[0.99674857,0.0001525281,0.00063579273,0.00165924,0.0005361757,0.00026770993],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0035741287,0.00012951836,0.00022855352,0.0006727954,0.00025703752,0.0018664607,0.013660817,0.000059127975,0.0000013078935],"category_scores_gemma":[0.0029810343,0.00010291356,0.00002411918,0.0016496641,0.00015068466,0.022650162,0.006072297,0.00018637923,0.000010722005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014900557,0.000028565166,0.0024984784,0.000042254618,0.000034593257,0.000006684393,0.0014068679,0.12046051,0.00041924842,0.005526889,0.06950066,0.7999262],"study_design_scores_gemma":[0.00068010326,0.000080819606,0.004075492,0.0000312411,0.000009702553,0.000021736929,0.0000312566,0.98784095,0.0001416133,0.0029287247,0.004029518,0.00012885986],"about_ca_topic_score_codex":0.0002302133,"about_ca_topic_score_gemma":0.00011461204,"teacher_disagreement_score":0.9372693,"about_ca_system_score_codex":0.00006851375,"about_ca_system_score_gemma":0.0007827184,"threshold_uncertainty_score":0.9991697},"labels":[],"label_agreement":null},{"id":"W4390046132","doi":"10.5311/josis.2023.27.307","title":"Reimagining GIScience education for enhanced employability","year":2023,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Geography Education and Pedagogy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Employability; Geography; Data science; Computer science; Sociology; Pedagogy","score_opus":0.043563901124714394,"score_gpt":0.42374678403213056,"score_spread":0.3801828829074162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390046132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7976028,0.000022967233,0.12560593,0.02193444,0.0125978505,0.00076627266,0.0000094854495,0.00012364106,0.041336663],"genre_scores_gemma":[0.9967855,0.000047447455,0.0022616002,0.0004045552,0.00031025847,0.0000120125,0.000002276011,0.0000016915213,0.00017462281],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982205,0.000042497282,0.0005030544,0.000085273925,0.0008735607,0.0002750842],"domain_scores_gemma":[0.9967603,0.00016101828,0.00056414,0.00011949057,0.0021988926,0.00019614269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055478746,0.000057123605,0.00010177417,0.0007896951,0.0008596871,0.00032580164,0.0005372598,0.000033427914,0.0000732059],"category_scores_gemma":[0.003283188,0.00004601835,0.00007501942,0.0017546314,0.0006677863,0.0050111488,0.000027037557,0.00010577818,0.00005195241],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004899275,0.00008917125,0.02562855,0.000034126148,0.000005560103,1.00405785e-7,0.09857659,0.0004943133,0.0033979856,0.025987064,0.003496606,0.8422409],"study_design_scores_gemma":[0.0006045577,0.00027932413,0.30425468,0.000087343076,0.00001819225,0.000006608074,0.059535574,0.0013574143,0.006062471,0.015878621,0.61157495,0.00034027433],"about_ca_topic_score_codex":0.001176718,"about_ca_topic_score_gemma":0.00015700715,"teacher_disagreement_score":0.84190065,"about_ca_system_score_codex":0.000120684585,"about_ca_system_score_gemma":0.005037588,"threshold_uncertainty_score":0.89364654},"labels":[],"label_agreement":null},{"id":"W4411012466","doi":"10.5311/josis.2025.30.389","title":"Opportunities and challenges of integrating geographic information science and large language models","year":2025,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Economic and Social Research Council; Tongji University; Alan Turing Institute","keywords":"Data science; Geographic information system; Computer science; Geography; Cartography","score_opus":0.04371017340372786,"score_gpt":0.3073972075832171,"score_spread":0.26368703417948924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411012466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7178429,0.0028220739,0.035422705,0.009219057,0.0015169797,0.00079955097,0.000034168665,0.00006786359,0.23227474],"genre_scores_gemma":[0.9941053,0.0050846855,0.0005418723,0.00023415458,0.000021817314,0.000003551059,5.550345e-7,9.307384e-7,0.000007174461],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9971408,0.000038893013,0.00095592794,0.000062329826,0.001526611,0.00027543335],"domain_scores_gemma":[0.99460685,0.000111398,0.0010924375,0.00011287294,0.003950868,0.00012555099],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009858452,0.00009764819,0.00022337833,0.0025164161,0.0011277335,0.00042906965,0.00041094614,0.000052930118,0.0000039486595],"category_scores_gemma":[0.0017200103,0.00008020553,0.000035946894,0.0015924249,0.0023288396,0.025530566,0.00018219341,0.00013650757,8.427881e-7],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015639427,0.000010879797,0.002036088,0.00016932034,0.000013810041,2.4828793e-7,0.2076743,0.000039250805,0.00005705685,0.63486177,0.000027507687,0.15509415],"study_design_scores_gemma":[0.0008849238,0.00016204092,0.034823522,0.00052187353,0.000028571352,0.000019770432,0.92179143,0.01101928,0.00034843694,0.0031490438,0.027018303,0.0002328192],"about_ca_topic_score_codex":0.0012931023,"about_ca_topic_score_gemma":0.0003332522,"teacher_disagreement_score":0.7141171,"about_ca_system_score_codex":0.000078984056,"about_ca_system_score_gemma":0.0010636211,"threshold_uncertainty_score":0.98809886},"labels":[],"label_agreement":null},{"id":"W7117358854","doi":"10.5311/josis.2025.31.462","title":"Spatial data science languages: commonalities and needs","year":2025,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Esri (Canada)","funders":"","keywords":"Software; Python (programming language); Domain (mathematical analysis); Focus (optics); Set (abstract data type); Spatial analysis; Scripting language; Geodetic datum; Software development","score_opus":0.022743537546909488,"score_gpt":0.31622203953093087,"score_spread":0.29347850198402137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117358854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0370356,0.00008812692,0.9509053,0.0023481143,0.00068578403,0.000080304286,0.000017808083,0.000026147494,0.008812793],"genre_scores_gemma":[0.98629093,0.000042690204,0.012641016,0.00093722594,0.00005107228,5.801382e-7,0.0000039411666,0.0000010856493,0.000031439435],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99738777,0.000027615259,0.0006983386,0.00016435774,0.0014536156,0.00026829433],"domain_scores_gemma":[0.99720126,0.000109070876,0.0005855448,0.00091861904,0.0010243255,0.00016116713],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0046931454,0.000103150676,0.00019888733,0.0019835674,0.00047069264,0.0017645954,0.0052693705,0.000025954629,0.000009269616],"category_scores_gemma":[0.0011992585,0.00008084709,0.000026978854,0.0033287725,0.0011475097,0.0329186,0.002021511,0.00018039867,0.000012453239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003591511,0.00006957485,0.01320867,0.00006551352,0.0000397936,0.00000942805,0.00762932,0.00040979474,0.0027062139,0.19994675,0.0027801264,0.7730989],"study_design_scores_gemma":[0.0012836803,0.0002651857,0.12118633,0.0002570519,0.000060936367,0.00024182505,0.0047311564,0.80827165,0.009710045,0.002283905,0.05123027,0.00047793725],"about_ca_topic_score_codex":0.0007478391,"about_ca_topic_score_gemma":0.000058789712,"teacher_disagreement_score":0.94925535,"about_ca_system_score_codex":0.00010036098,"about_ca_system_score_gemma":0.0015923026,"threshold_uncertainty_score":0.9992717},"labels":[],"label_agreement":null}]}