{"id":"W6913303480","doi":"10.5683/sp3/m5o0v4","title":"UNI-CEN Boundaries (CBF-Original Shorelines) - Census Metropolitan Area (CMA) - 1981 - Esri Shapefile format (NAD83 CSRS / EPSG:3348)","year":2023,"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","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":[0.001359178,0.001868886,0.001440959,0.004854633,0.001053793,0.002628698,0.003102415,0.001073978,0.1130373],"category_scores_gemma":[0.005802537,0.001185414,0.0009180422,0.0138752,0.0004103141,0.001893226,0.002331336,0.001922388,0.1957544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00319153,"about_ca_system_score_gemma":0.004854023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1232793,"about_ca_topic_score_gemma":0.1701531,"domain_scores_codex":[0.9983525,0.0001909887,0.0002068234,0.0004144094,0.0005084742,0.000326872],"domain_scores_gemma":[0.9964271,0.000372165,0.0003184129,0.000987467,0.001593274,0.0003015524],"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":[0.00002082843,0.000007059663,0.000602672,0.000185266,0.000009271915,0.000008892393,0.00002594824,0.00005973746,0.0000664851,0.0004486463,0.9973785,0.001186791],"study_design_scores_gemma":[0.00005075228,0.000004029468,0.004569422,0.0001130462,0.000007598904,0.00002027557,0.0001003192,0.0000719044,0.0001978542,0.00039358,0.9944552,0.00001613238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000636797,0.0000120607,0.00003837648,0.00001936466,0.00001128063,0.000006377485,0.9987699,0.0001473651,0.0009316276],"genre_scores_gemma":[0.00019235,0.00001959866,0.000166885,0.00001259333,0.000002637254,0.00004595255,0.9986511,0.00008066662,0.000828257],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8767207,"threshold_uncertainty_score":0.3781475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04160161344307788,"score_gpt":0.3057571081948585,"score_spread":0.2641554947517806,"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."}}