{"id":"W6950816217","doi":"10.5683/sp3/rdk0kk","title":"UNI-CEN Boundaries (CBF-Harmonized Shorelines) - Census Metropolitan Area (CMA) - 1996 - File Geodatabase format (NAD83 CSRS / EPSG:3348)","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Shapefile; North American Datum of 1927; File format; Census; Documentation; Geocoding; Boundary (topology); Metropolitan area; Data file","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001529608,0.001820881,0.001350356,0.004642057,0.0009471691,0.002549773,0.003334257,0.001061616,0.101206],"category_scores_gemma":[0.006546574,0.001166685,0.000972581,0.01378349,0.0003530971,0.001920104,0.002421755,0.001940693,0.1537134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003064876,"about_ca_system_score_gemma":0.004792919,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1210333,"about_ca_topic_score_gemma":0.1535667,"domain_scores_codex":[0.9984512,0.0001929429,0.0002051838,0.0004007562,0.0004666167,0.0002832196],"domain_scores_gemma":[0.9963606,0.0003447925,0.000343898,0.001025295,0.001634093,0.000291361],"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":[0.00002812655,0.000008044993,0.0008048807,0.0002062688,0.00001254708,0.00001063789,0.00002789801,0.00008085223,0.00007269983,0.000515304,0.9968555,0.001377224],"study_design_scores_gemma":[0.00006507269,0.000004727311,0.005253424,0.0001416682,0.000009087942,0.00002296638,0.0001073982,0.0001012097,0.0002566523,0.0004402476,0.9935791,0.00001834472],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000741051,0.00001106013,0.00004371247,0.00002095676,0.00001199291,0.000007006157,0.9988895,0.0001550463,0.0007865764],"genre_scores_gemma":[0.0002262486,0.00001805948,0.0002001395,0.00001281007,0.000002496222,0.00005336919,0.9986668,0.0000827937,0.0007374022],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8789667,"threshold_uncertainty_score":0.3385679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03698587602860288,"score_gpt":0.285033498279471,"score_spread":0.2480476222508681,"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."}}