{"id":"W6989843121","doi":"","title":"Canada VMap1, Library 23: Power Lines","year":2016,"lang":"en","type":"other","venue":"The Faculty Digital Archive (New York University)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scale (ratio); Product (mathematics); Vector map; Base (topology); Geographic information system; Digital mapping; Topographic map (neuroanatomy); Power (physics)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000395552,0.001038814,0.0004806391,0.004605242,0.003822693,0.005191156,0.001817012,0.0005618136,0.369161],"category_scores_gemma":[0.003241092,0.0005743004,0.0003408749,0.01758506,0.0005040598,0.001953137,0.0009702736,0.0007759302,0.1429711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02004498,"about_ca_system_score_gemma":0.04388202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.947448,"about_ca_topic_score_gemma":0.954115,"domain_scores_codex":[0.9989397,0.00003529051,0.0000276459,0.0001057622,0.0007427387,0.0001488552],"domain_scores_gemma":[0.9973533,0.00008249524,0.00005766658,0.0001733015,0.002140296,0.0001928675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001683793,0.000007603208,0.0003780575,0.00008310867,0.000002366907,0.00002656543,0.00008848331,0.00032016,0.0001077439,0.003533806,0.9517596,0.04367568],"study_design_scores_gemma":[0.000003969433,0.00000196468,0.001170832,0.00002968153,0.000002076739,0.00001962104,0.0000640063,0.0001930962,0.0001495769,0.0003810581,0.9979759,0.00000817321],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.00149458,0.0006793434,0.003955007,0.0005707787,0.0001589492,0.0001861859,0.202367,0.006383965,0.7842044],"genre_scores_gemma":[0.01546006,0.002247125,0.006885058,0.0002356532,0.0000822586,0.0001500926,0.1526114,0.003585865,0.8187426],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.369161,"threshold_uncertainty_score":0.8998153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517454098314366,"score_gpt":0.2084039150170232,"score_spread":0.1932293740338796,"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."}}