{"id":"W2075870772","doi":"10.12927/hcq.2009.21100","title":"Improving Patient Access to Medical Services: Preventing the Patient from Being Lost in Translation","year":2009,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Triage; Service (business); Prioritization; Process (computing); Best practice; Point of care; Primary care; Health care; Process management; Business; Medicine; Nursing; Medical emergency; Computer science; Family medicine; Marketing; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009997381,0.0002236646,0.0003182695,0.000181553,0.001027051,0.00009217401,0.0003436408,0.0003514326,0.0002536677],"category_scores_gemma":[0.0001331522,0.000175965,0.00005899048,0.0005929322,0.00001359852,0.0004582036,0.00003212634,0.0009743572,0.000095364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003049585,"about_ca_system_score_gemma":0.0009992602,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01784162,"about_ca_topic_score_gemma":0.0340343,"domain_scores_codex":[0.9953152,0.00133024,0.001424748,0.0005129392,0.0006719081,0.000744983],"domain_scores_gemma":[0.9980037,0.0004350505,0.0003003452,0.0004570603,0.0003008277,0.0005030077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000719698,0.00009406318,0.0107343,0.0002226163,0.000005187672,0.00001172664,0.1132139,0.0003272292,0.00005513913,0.0003729607,0.00008170621,0.8748092],"study_design_scores_gemma":[0.006494596,0.009725735,0.3709466,0.01757088,0.00009172333,0.0000172485,0.1760692,0.3863957,0.0001581574,0.007741574,0.02201205,0.002776593],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.901898,0.0002966805,0.005704115,0.08793355,0.0007619419,0.002754029,0.000036289,0.0001026153,0.0005127882],"genre_scores_gemma":[0.9694448,0.00002542953,0.003237418,0.02657286,0.0003442396,0.0001944876,0.0001409774,0.00002755785,0.0000122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8720326,"threshold_uncertainty_score":0.9886987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03987573614724943,"score_gpt":0.3906521586402131,"score_spread":0.3507764224929636,"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."}}