{"id":"W6950793118","doi":"10.5683/sp3/hs82ak","title":"UNI-CEN Boundaries (CBF-Harmonized Shorelines) - Census Metropolitan Area (CMA) - 2016 - Esri Shapefile 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","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":[0.001458065,0.001803809,0.001378886,0.004308375,0.0009397253,0.002622639,0.003204586,0.001078926,0.1046769],"category_scores_gemma":[0.006244913,0.001162614,0.001019313,0.01137661,0.0003855731,0.002042401,0.002660761,0.001939299,0.1642649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002538765,"about_ca_system_score_gemma":0.004458077,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1062001,"about_ca_topic_score_gemma":0.1581276,"domain_scores_codex":[0.9984455,0.0002058575,0.0002038031,0.0003882812,0.0004591876,0.000297429],"domain_scores_gemma":[0.9965923,0.0003282013,0.0003131166,0.0009672235,0.001505553,0.0002934373],"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":[0.00002205435,0.000007249825,0.0007074141,0.0002211603,0.00001127422,0.000009226233,0.000029019,0.00006953248,0.00007101093,0.0005166885,0.997039,0.001296408],"study_design_scores_gemma":[0.00005759096,0.000004267478,0.004197722,0.0001466844,0.00000845537,0.0000226358,0.0001106635,0.00009450516,0.0002060049,0.0004975949,0.9946359,0.00001807475],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006918523,0.00001292034,0.00005365338,0.00002248443,0.00001422738,0.000007246115,0.9987541,0.0001945538,0.0008715903],"genre_scores_gemma":[0.0002478724,0.00002145589,0.0002529173,0.00001672087,0.000003219147,0.00005593084,0.998535,0.0001129891,0.0007537699],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8938,"threshold_uncertainty_score":0.350179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03622204542751897,"score_gpt":0.2850098908788652,"score_spread":0.2487878454513462,"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."}}