{"id":"W2097410730","doi":"10.12927/hcq..18222","title":"CIHI Survey: Wait Times: A Snapshot of What We Know","year":2006,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Snapshot (computer storage); Best practice; Medicine; Computer science; Political science; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002860205,0.0003763126,0.0006180686,0.003817659,0.0004749942,0.001488309,0.0009860599,0.001291012,0.004029798],"category_scores_gemma":[0.01096023,0.0003808729,0.0005750807,0.009317581,0.000239176,0.002832993,0.001142537,0.002032425,0.001178403],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002553728,"about_ca_system_score_gemma":0.004768565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1136634,"about_ca_topic_score_gemma":0.1814843,"domain_scores_codex":[0.998254,0.0004521547,0.0004450327,0.0001737363,0.0003296376,0.0003454266],"domain_scores_gemma":[0.9794851,0.005693139,0.0045365,0.0006948527,0.006325569,0.003264811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004642496,0.0003454468,0.6659288,0.002721679,0.0002653841,0.0001487864,0.002600732,0.0003762944,0.0003407203,0.0006150537,0.1912016,0.1349913],"study_design_scores_gemma":[0.00002817547,0.0001659396,0.948999,0.0007694452,0.0001401946,0.000196864,0.004154139,0.0002733337,0.0002370585,0.0001850611,0.04477044,0.00008037213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5395758,0.06620473,0.00468631,0.08953399,0.002235481,0.0002970342,0.255983,0.0009856748,0.040498],"genre_scores_gemma":[0.8584859,0.03951329,0.004842435,0.01482889,0.001888049,0.0004576921,0.07248385,0.0002543352,0.007245381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9974463,"threshold_uncertainty_score":0.2260036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02799103650586782,"score_gpt":0.3092612161274875,"score_spread":0.2812701796216197,"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."}}