{"id":"W6920826282","doi":"10.6084/m9.figshare.21501241.v1","title":"Additional file 2 of Pharmacy location and medical need: regional evidence from Canada","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pharmacy; Table (database); MEDLINE; Medical prescription; Payment; Real world evidence","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":[0.001340087,0.0006289168,0.0009606736,0.003321812,0.001348597,0.001396479,0.002008113,0.0008727284,0.6639106],"category_scores_gemma":[0.03205302,0.0005132713,0.00121081,0.008165415,0.0002883166,0.00137951,0.0008795103,0.001086116,0.04299786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005786934,"about_ca_system_score_gemma":0.01189675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7866083,"about_ca_topic_score_gemma":0.7989758,"domain_scores_codex":[0.9988136,0.0001511762,0.0001691763,0.0001704973,0.0004486766,0.0002469222],"domain_scores_gemma":[0.9695729,0.01521499,0.002608778,0.001337916,0.01046828,0.0007970956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009238837,0.00003633479,0.007867127,0.0009077396,0.00004223318,0.00002642079,0.00007715121,0.0002946458,0.00001107344,0.0007115539,0.9861404,0.003792968],"study_design_scores_gemma":[0.002939689,0.0001279482,0.2600569,0.006187658,0.0003845984,0.0002871011,0.002316079,0.003160662,0.0003620298,0.004742786,0.7192516,0.0001831115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003378876,0.00003171743,0.00004803845,0.0001168453,0.00001068334,0.00004392485,0.9979835,0.00003236592,0.001395],"genre_scores_gemma":[0.03651652,0.0003910598,0.001980606,0.000601672,0.00007500761,0.001344966,0.9346645,0.0002311728,0.02419451],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6639106,"threshold_uncertainty_score":0.4793907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1035645233592447,"score_gpt":0.312571033243341,"score_spread":0.2090065098840963,"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."}}