{"id":"W6939025486","doi":"10.6068/dp14ba7c98cef44","title":"Trend 2000 - 2003. Statistics Canada. CANSIM: Transportation - Transportation by Road | Country: Canada | Table: Canadian vehicle survey, number of vehicles on the registration lists, by type of vehicle, province and territory | Variable: Buses | Units: # Units, 2000-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-197.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Taxis; Economic statistics; Official statistics; Summary statistics; Statistical analysis; Socioeconomic status; Transit (satellite)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002336448,0.002509041,0.002677435,0.008286224,0.003372384,0.004851454,0.005109354,0.001449621,0.09993135],"category_scores_gemma":[0.01876436,0.001813491,0.002206117,0.04078736,0.0006276228,0.002800104,0.002204907,0.003192913,0.06215105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05513406,"about_ca_system_score_gemma":0.1370905,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953857,"about_ca_topic_score_gemma":0.9933201,"domain_scores_codex":[0.9955439,0.000348519,0.0004624843,0.0005878872,0.002083193,0.0009740808],"domain_scores_gemma":[0.9673797,0.001076401,0.0008704348,0.001048317,0.02816088,0.001464275],"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":[0.00002114692,0.000005880502,0.000877558,0.0002075716,0.00001922909,0.000006422537,0.00002209783,0.0001287056,0.000008743425,0.0004537215,0.9964213,0.0018275],"study_design_scores_gemma":[0.0001223655,0.00001141929,0.01866574,0.000737349,0.00006737391,0.00002531038,0.0004307686,0.0005922698,0.0001487863,0.0007818082,0.97833,0.00008676048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005512134,0.00005733703,0.00004336086,0.0001443315,0.00003696055,0.00001880849,0.9982968,0.00008697745,0.00126033],"genre_scores_gemma":[0.0009784143,0.0003283632,0.0006058496,0.0001927088,0.00001957942,0.00015747,0.9922564,0.0001853731,0.005275815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9000686,"threshold_uncertainty_score":0.4000275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0267756156344123,"score_gpt":0.2422705268160058,"score_spread":0.2154949111815935,"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."}}