{"id":"W6931516843","doi":"10.5683/sp3/chytrw","title":"UNI-CEN Boundaries (CBF-Harmonized Shorelines) - Federal Electoral District (FED) - 1947 - Esri Shapefile format (NAD83 CSRS / EPSG:3348)","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Psychological Well-being and Life Satisfaction","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Shapefile; North American Datum of 1927; File format; Documentation; Census; Boundary (topology); Geocoding; 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":[0.001339947,0.001221724,0.001172655,0.003897515,0.000918198,0.002197015,0.002455263,0.0009195931,0.05853032],"category_scores_gemma":[0.00602449,0.0009412523,0.0007022199,0.008871829,0.0003819222,0.001095084,0.001952428,0.00171081,0.07978337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002754299,"about_ca_system_score_gemma":0.004298986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1546414,"about_ca_topic_score_gemma":0.2136972,"domain_scores_codex":[0.9987898,0.0001937458,0.0001406305,0.0002939262,0.0003261391,0.0002558204],"domain_scores_gemma":[0.9970918,0.000327973,0.0003245374,0.0007134715,0.001261845,0.0002804125],"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":[0.00003835702,0.00001581527,0.002110398,0.0001790276,0.00001518306,0.00001182506,0.00003919872,0.00009584468,0.00004420706,0.0004956821,0.9951761,0.00177845],"study_design_scores_gemma":[0.0001048711,0.000008566074,0.01987857,0.0001507186,0.00001394216,0.00003324152,0.0001894677,0.0001740841,0.0002502257,0.0004361774,0.978738,0.00002205959],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002638632,0.00001877354,0.00005816174,0.00002820982,0.00001464584,0.00001090403,0.9982929,0.0001526104,0.001159968],"genre_scores_gemma":[0.0006202798,0.00001996308,0.0002259597,0.00001757792,0.000004312078,0.00007769994,0.9978033,0.00005608827,0.001174853],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8453586,"threshold_uncertainty_score":0.3074827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03148924616325052,"score_gpt":0.3175751502625058,"score_spread":0.2860859040992553,"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."}}