{"id":"W6901478132","doi":"10.6068/dp14ba7c8a97455","title":"Trend 2000 - 2009. Statistics Canada. CANSIM: Transportation - Transportation by Road | Country: Canada | Table: Canadian vehicle survey, number of trucks 15 tonnes and over, by year of vehicle model, province and territory | Variable: Current year | Units: # Units, 2000-2009. 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":"Truck; Taxis; Economic statistics; Census; Summary statistics; Official statistics; Statistical analysis; Descriptive statistics","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":[0.002051451,0.002378245,0.00248344,0.007502212,0.003226632,0.004414958,0.004833397,0.001367914,0.09804434],"category_scores_gemma":[0.01783193,0.0017042,0.002152989,0.03670866,0.0005821865,0.002636673,0.002103554,0.003003109,0.05691602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05098492,"about_ca_system_score_gemma":0.12378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954483,"about_ca_topic_score_gemma":0.9934757,"domain_scores_codex":[0.9959373,0.0002877314,0.0004375115,0.0005422555,0.001889395,0.0009057191],"domain_scores_gemma":[0.9697381,0.0009849602,0.0008098976,0.0009367921,0.02620958,0.001320609],"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":[0.00002382114,0.000006237199,0.001045157,0.0002411209,0.00002050515,0.000007224033,0.00002185177,0.0001441824,0.000009918724,0.0004473861,0.9960211,0.002011569],"study_design_scores_gemma":[0.0001364422,0.00001325809,0.02296537,0.0008423023,0.00007441679,0.00002939212,0.0004517993,0.0006566407,0.0001691427,0.000747563,0.9738204,0.00009326109],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005906966,0.0000573151,0.00004131942,0.0001291484,0.00003548358,0.00001805666,0.9983538,0.00007886902,0.001226927],"genre_scores_gemma":[0.00109226,0.0003566422,0.0005920765,0.0001876385,0.00002003085,0.0001447474,0.9923131,0.0001608086,0.005132786],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09804434,"threshold_uncertainty_score":0.3699232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847857136567802,"score_gpt":0.2387365007111571,"score_spread":0.2202579293454791,"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."}}