{"id":"W6945376752","doi":"10.25318/2310030501-eng","title":"Ridership by linked origin and destination trips, in urban transit, by industry","year":2022,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Table (database); Urban transit; Destinations; Public transport","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004515219,0.001162087,0.001076184,0.004723477,0.001038238,0.0018486,0.001781521,0.0005973137,0.03902874],"category_scores_gemma":[0.004900192,0.000533571,0.0009702459,0.01549891,0.0002674336,0.0007928315,0.0008983005,0.001190184,0.01687861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005499765,"about_ca_system_score_gemma":0.008501961,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8856551,"about_ca_topic_score_gemma":0.9134651,"domain_scores_codex":[0.9990537,0.00004306204,0.0001003584,0.0002098649,0.0003397572,0.0002531761],"domain_scores_gemma":[0.9970367,0.0002619764,0.0002932734,0.0002191228,0.001900902,0.0002881069],"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":[0.00004809991,0.00001676961,0.009527489,0.0003970334,0.00005750188,0.00001815833,0.00005463752,0.0004654504,0.00003440783,0.0005442539,0.9857075,0.003128724],"study_design_scores_gemma":[0.0002061107,0.00002955843,0.1772817,0.0007394599,0.0001199242,0.00007533583,0.0006158274,0.001306557,0.0003247518,0.000514466,0.8187118,0.00007443075],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005161957,0.00005055,0.00002197232,0.00002688728,0.00001018729,0.000008887836,0.9985496,0.00003648644,0.0007791227],"genre_scores_gemma":[0.00287857,0.0001284251,0.000115877,0.00002896533,0.000007019075,0.00005954294,0.9946105,0.000024157,0.002146998],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1143449,"threshold_uncertainty_score":0.2300366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388686264944615,"score_gpt":0.2512385443610597,"score_spread":0.2373516817116136,"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."}}