{"id":"W6969302957","doi":"10.5683/sp3/hnimf8","title":"UNI-CEN Boundaries (CBF-Original Shorelines) - Census Metropolitan Area (CMA) - 1991 - File Geodatabase format (NAD83 CSRS / EPSG:3348)","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"SAS software applications and methods","field":"Engineering","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":[0.001913453,0.001349216,0.001228698,0.004933245,0.0007943075,0.002108727,0.002489981,0.0008748857,0.112245],"category_scores_gemma":[0.01080994,0.0008914809,0.0007837284,0.01408611,0.0003228773,0.001447066,0.002055094,0.001805221,0.1365832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003187625,"about_ca_system_score_gemma":0.006404901,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1037439,"about_ca_topic_score_gemma":0.1200937,"domain_scores_codex":[0.9980896,0.0002645888,0.0002934533,0.0004450224,0.0005832813,0.000324113],"domain_scores_gemma":[0.9939373,0.0008133003,0.0006358799,0.001267495,0.002971645,0.0003743135],"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":[0.00003243029,0.00000819598,0.001275666,0.0002322227,0.00001364579,0.000009602965,0.00002992018,0.00008698011,0.0000570038,0.0007726984,0.9956927,0.001789039],"study_design_scores_gemma":[0.00007172837,0.000005836436,0.008623551,0.0001606427,0.00001066498,0.00002208798,0.0001122406,0.00009298138,0.0002268556,0.0004721192,0.9901841,0.00001716921],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000111811,0.00001355,0.00007324649,0.00002548255,0.000012812,0.00001264193,0.9984875,0.0001311432,0.001131832],"genre_scores_gemma":[0.0004000879,0.00002695681,0.000358477,0.00001979831,0.000004280231,0.0001163811,0.9977539,0.0001067668,0.001213316],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.896256,"threshold_uncertainty_score":0.375497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03310932705112328,"score_gpt":0.2991833539959484,"score_spread":0.2660740269448251,"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."}}