{"id":"W3081427707","doi":"10.5194/isprs-archives-xliii-b4-2020-261-2020","title":"INTEGRATION OF AUTHORITATIVE AND VOLUNTEERED GEOGRAPHIC INFORMATION FOR UPDATING URBAN MAPPING: CHALLENGES AND POTENTIALS","year":2020,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volunteered geographic information; Conflation; Library science; Geographic information system; Data science; Geography; Web of science; Information retrieval; Regional science; Computer science; Cartography; Political science; MEDLINE","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04759781,0.0006460226,0.001727899,0.0519807,0.001593397,0.01963975,0.00226048,0.001339947,0.003173961],"category_scores_gemma":[0.1261469,0.0004935241,0.0010997,0.09748414,0.003171231,0.01741095,0.004771204,0.0009551625,0.0008077933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004934549,"about_ca_system_score_gemma":0.008485816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005507754,"about_ca_topic_score_gemma":0.006561862,"domain_scores_codex":[0.9399726,0.03013688,0.00475928,0.002533564,0.02161752,0.0009801802],"domain_scores_gemma":[0.7802377,0.1315875,0.01859996,0.01528867,0.052233,0.002053142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001196166,0.0001126273,0.07307895,0.01732861,0.000723813,0.0002881188,0.007314666,0.001919484,0.0007664509,0.04668956,0.01532429,0.8363338],"study_design_scores_gemma":[0.00006927764,0.0005070692,0.1844763,0.04967158,0.002444157,0.002050043,0.06816061,0.01559219,0.005120825,0.06166979,0.6098922,0.0003459508],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.195438,0.5441588,0.06161444,0.0498461,0.002482582,0.0009105858,0.007274408,0.0005926047,0.1376826],"genre_scores_gemma":[0.8051642,0.1424308,0.04199489,0.001372697,0.002067118,0.0004242753,0.003151971,0.0001771109,0.00321687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0519807,"threshold_uncertainty_score":0.2517243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03983572820313241,"score_gpt":0.2799614056622549,"score_spread":0.2401256774591224,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}