{"id":"W3185626603","doi":"10.29173/cjen137","title":"Time modifier billing code - an interrupted time series analysis","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Nursing","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Observational study; Cohort; Government (linguistics); Emergency department; Interrupted Time Series Analysis; Code (set theory); Confidence interval; Diagnosis code; Interrupted time series; Emergency medicine; Retrospective cohort study; Medical emergency; Family medicine; Demography; Computer science; Psychological intervention; Nursing; Environmental health; Statistics; Population; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.02907823,0.0005084727,0.001062196,0.002513751,0.0004452978,0.00147281,0.001611546,0.001062407,0.002546379],"category_scores_gemma":[0.07627591,0.0003954106,0.002829529,0.004773131,0.0006953315,0.001050568,0.001144119,0.002484299,0.0003319998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001443546,"about_ca_system_score_gemma":0.001194776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0181154,"about_ca_topic_score_gemma":0.007026781,"domain_scores_codex":[0.9845842,0.01018061,0.0011809,0.001533734,0.001862379,0.0006583161],"domain_scores_gemma":[0.8878078,0.08798499,0.01492911,0.005201661,0.002983744,0.001092664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001539158,0.0004036385,0.9377689,0.0003824259,0.002538078,0.0004363531,0.001429072,0.009059596,0.0003112034,0.003557329,0.003485415,0.03908887],"study_design_scores_gemma":[0.0001512856,0.001298049,0.7537614,0.0003369658,0.001746593,0.0004739996,0.00170642,0.2295144,0.0006081556,0.004403933,0.005865228,0.0001335411],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9306716,0.003413446,0.0562713,0.001987978,0.0003550416,0.0006884625,0.004550388,0.0001783029,0.001883639],"genre_scores_gemma":[0.9819959,0.0005426254,0.01251651,0.0001580178,0.0001118276,0.0006005104,0.003159232,0.00004474491,0.0008706072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02907823,"threshold_uncertainty_score":0.1537822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08474427918318606,"score_gpt":0.4267628521804607,"score_spread":0.3420185729972747,"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."}}