{"id":"W6902176817","doi":"10.6084/m9.figshare.22786040.v1","title":"Quantifying HCP Burden of REMS Programs","year":2023,"lang":"en","type":"article","venue":"Open MIND","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Health care; Test (biology); Simple (philosophy); Data collection; MEDLINE","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":[0.003494872,0.0004938034,0.0003440951,0.0008460359,0.000351984,0.0009422217,0.0007439637,0.0004072601,0.00284605],"category_scores_gemma":[0.01957902,0.0002444029,0.0005093696,0.000954684,0.0002839456,0.001091705,0.0006785376,0.0005379684,0.0001903155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002435452,"about_ca_system_score_gemma":0.002145436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02604813,"about_ca_topic_score_gemma":0.02289327,"domain_scores_codex":[0.996942,0.001677424,0.0001421094,0.0002658415,0.000673794,0.0002987056],"domain_scores_gemma":[0.9847383,0.01015421,0.001768378,0.001272386,0.001768677,0.0002979948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003570371,0.0002659918,0.1155678,0.0001018809,0.0001331492,0.0001220369,0.0002429236,0.8335511,0.001726622,0.00765824,0.001349202,0.03892401],"study_design_scores_gemma":[0.00002671786,0.0004087454,0.04695653,0.00003641424,0.00004512969,0.00008937801,0.0005323993,0.9448181,0.001633736,0.003722582,0.001705918,0.00002425281],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9439282,0.0001655458,0.03847694,0.001169484,0.00004703274,0.0003134026,0.001918031,0.0001768539,0.01380443],"genre_scores_gemma":[0.9868228,0.00008498452,0.0113843,0.00005816898,0.00001374893,0.0000514041,0.0005443402,0.00001414639,0.001026011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02604813,"threshold_uncertainty_score":0.05179304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4218614097774904,"score_gpt":0.5403137257605803,"score_spread":0.11845231598309,"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."}}