{"id":"W6958596462","doi":"10.6084/m9.figshare.23714217","title":"Additional file 1 of Predictive risk modelling of high resource users under different prescription drug coverage policies in Ontario and Manitoba, Canada","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Vector Institute; University of Manitoba; Trillium Health Centre; University of Toronto","funders":"","keywords":"Prescription drug; Resource (disambiguation); Medical prescription; Risk assessment; Health care; Drug; MEDLINE","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007089319,0.0006598158,0.0007812738,0.001943215,0.001129033,0.001408654,0.001730471,0.0007022996,0.4716077],"category_scores_gemma":[0.01144335,0.000528247,0.001016275,0.004989998,0.0002604518,0.0005931239,0.0005820523,0.0006127415,0.02734086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01135944,"about_ca_system_score_gemma":0.0206065,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9552249,"about_ca_topic_score_gemma":0.9676176,"domain_scores_codex":[0.9996437,0.00004038528,0.0000401696,0.00006752821,0.0001075171,0.0001007875],"domain_scores_gemma":[0.9934959,0.002811684,0.0003353965,0.000337885,0.002753593,0.0002654957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001076404,0.00006033919,0.0210295,0.0007914907,0.00007817449,0.00007295453,0.0001406309,0.007107382,0.00004752451,0.001949827,0.9597013,0.008913193],"study_design_scores_gemma":[0.002453589,0.0001068401,0.1777205,0.00213096,0.0003161783,0.0002590316,0.001390016,0.04056592,0.0005377927,0.007099337,0.7672275,0.0001923594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0006710794,0.00001644453,0.0001442606,0.00006767734,0.000008164321,0.00004012332,0.9975116,0.00006906213,0.001471522],"genre_scores_gemma":[0.04594563,0.0002263318,0.004315616,0.0001995212,0.0000335728,0.0006629924,0.9350955,0.0002321867,0.01328858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4716077,"threshold_uncertainty_score":0.7536874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05830286382285253,"score_gpt":0.2198064213057084,"score_spread":0.1615035574828559,"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."}}