{"id":"W2138121058","doi":"","title":"Taking control of your appointment schedule. Part 2: Establishing expectations and scheduling with computers.","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"Hospital Admissions and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Scheduling (production processes); Schedule; Control (management); Data science; Operations research; Artificial intelligence; Operations management; Operating system; Engineering","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":[0.006507238,0.0006216553,0.0003979385,0.0007866372,0.0009081045,0.001695229,0.001109361,0.001003588,0.01709031],"category_scores_gemma":[0.04083772,0.0004878968,0.0003879492,0.0005757534,0.0004529316,0.001460509,0.0009432952,0.001310865,0.005912767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001228335,"about_ca_system_score_gemma":0.003860975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005325457,"about_ca_topic_score_gemma":0.007604617,"domain_scores_codex":[0.9964854,0.001740118,0.0003293578,0.0001400349,0.001022289,0.0002827962],"domain_scores_gemma":[0.9800373,0.01017615,0.002959912,0.001280267,0.002427056,0.003119372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003704857,0.001086168,0.03472917,0.0004785067,0.00002366036,0.0001360651,0.001664162,0.0008951602,0.002294089,0.001116285,0.1313201,0.8258861],"study_design_scores_gemma":[0.0003780244,0.003149592,0.4970922,0.00324059,0.0001583336,0.002397672,0.008854879,0.007779979,0.01964671,0.01059922,0.4463453,0.0003575392],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.3413732,0.02641545,0.1539338,0.1111843,0.008377524,0.008074455,0.005262871,0.0104198,0.3349585],"genre_scores_gemma":[0.7572733,0.01666766,0.1439379,0.008658201,0.003540375,0.003738465,0.00273888,0.001117482,0.06232778],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01709031,"threshold_uncertainty_score":0.05717283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02817677652512879,"score_gpt":0.2519242070832955,"score_spread":0.2237474305581668,"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."}}