{"id":"W2241642306","doi":"","title":"Ontario Commercial Vehicle Survey: Use of Geographic Information Systems for Data Collection, Processing, Analysis, and Dissemination","year":2008,"lang":"en","type":"article","venue":"","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Transport engineering; Data collection; Geographic information system; Survey data collection; Data processing; Travel survey; Christian ministry; Commodity; Business; Geography; Computer science; Engineering; Travel behavior; Database; Remote sensing; Finance","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":[0.003959486,0.0009984466,0.001275366,0.006012452,0.002218526,0.002295741,0.001733465,0.0004051474,0.02343399],"category_scores_gemma":[0.01220926,0.0007359711,0.0005258447,0.02131431,0.0005757581,0.001335496,0.001450867,0.0008346308,0.006749681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03183563,"about_ca_system_score_gemma":0.1045464,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9784341,"about_ca_topic_score_gemma":0.9794632,"domain_scores_codex":[0.9934262,0.0005540431,0.0005362999,0.0004501053,0.004657,0.0003763369],"domain_scores_gemma":[0.974903,0.0009389723,0.001173695,0.0009414933,0.02119518,0.0008476159],"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":[0.0001240267,0.00006930817,0.04367128,0.001310281,0.0001128182,0.00008310781,0.0009728962,0.0009640459,0.0006762616,0.002134807,0.8175197,0.1323615],"study_design_scores_gemma":[0.0001245255,0.00003616515,0.3031468,0.0005091422,0.00008919305,0.00005909158,0.0009433335,0.002362294,0.0005266077,0.0006277765,0.6914888,0.00008635987],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01217958,0.001522813,0.01150042,0.002353502,0.0002259945,0.003678645,0.8739147,0.001914028,0.09271038],"genre_scores_gemma":[0.09660578,0.006546698,0.05422226,0.0008102802,0.0001382527,0.008312448,0.7610301,0.001099365,0.07123481],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03183563,"threshold_uncertainty_score":0.2309847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05889187430962305,"score_gpt":0.2781339133636993,"score_spread":0.2192420390540762,"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."}}