{"id":"W7017600278","doi":"","title":"Back on track : Ontario's remedial measures program for impaired drivers","year":2003,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Track (disk drive); Remedial education; Training (meteorology); Noise (video); Data collection","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":[0.0002798858,0.0003374572,0.0002747895,0.001111639,0.002541217,0.0008456837,0.001190823,0.001112833,0.07634526],"category_scores_gemma":[0.001445009,0.0002960875,0.0002732034,0.0008837702,0.0002264639,0.0003844308,0.0009183244,0.0005958499,0.01093239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006251708,"about_ca_system_score_gemma":0.0413844,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9264081,"about_ca_topic_score_gemma":0.9835947,"domain_scores_codex":[0.9996773,0.00001339306,0.00001437682,0.00001559268,0.0001478422,0.0001314521],"domain_scores_gemma":[0.9985708,0.00005300673,0.00006556709,0.000041096,0.0006518363,0.0006175817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003682881,0.001102666,0.03268715,0.0002221022,0.00001179848,0.0003653325,0.0005478025,0.0001308798,0.0006162838,0.0001773224,0.7872726,0.1764977],"study_design_scores_gemma":[0.000518913,0.0004563046,0.610381,0.000427642,0.00006727304,0.0001866661,0.001670282,0.000413599,0.0005061671,0.0001780353,0.3851615,0.00003268561],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2111532,0.005299,0.0006286887,0.02090704,0.001828713,0.003469649,0.07997423,0.001497929,0.6752416],"genre_scores_gemma":[0.1891707,0.003921984,0.001117119,0.004145123,0.0002525636,0.0007227884,0.01136887,0.0001583994,0.7891424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07634526,"threshold_uncertainty_score":0.2554004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02144690909615682,"score_gpt":0.2728493770693883,"score_spread":0.2514024679732315,"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."}}