{"id":"W7097259095","doi":"","title":"References","year":2004,"lang":"en","type":"article","venue":"","topic":"Pharmaceutical industry and healthcare","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical prescription; Government (linguistics); State (computer science); Agency (philosophy)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008271604,0.0007970625,0.0007094821,0.004065189,0.001800146,0.002424305,0.001618373,0.002438202,0.4330187],"category_scores_gemma":[0.006496377,0.0002608648,0.0008410124,0.002749105,0.0006201864,0.001924387,0.001239659,0.002319496,0.3119064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002540041,"about_ca_system_score_gemma":0.003345515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02126035,"about_ca_topic_score_gemma":0.02440148,"domain_scores_codex":[0.9989679,0.0001474563,0.00007507625,0.0001206609,0.0005849947,0.000104067],"domain_scores_gemma":[0.9976366,0.0004099295,0.00008896065,0.0001643075,0.001539764,0.0001604878],"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":[0.00001850449,0.00002541891,0.000200226,0.0002564317,0.000003500767,0.0001452723,0.00009367774,0.0000626485,0.0000937918,0.009415108,0.9359775,0.05370783],"study_design_scores_gemma":[0.000002396281,0.000003262219,0.0002419402,0.000241429,0.000002312735,0.0001546766,0.00004943836,0.00001147723,0.00004513359,0.001484788,0.9977591,0.000003941846],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006317036,0.04409142,0.003200245,0.02929789,0.03178062,0.0003386364,0.008475222,0.0005521194,0.8816321],"genre_scores_gemma":[0.005753549,0.02817524,0.003496255,0.01225588,0.003889153,0.0001576605,0.007365901,0.0003510457,0.9385554],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5669813,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7223968300008685,"score_gpt":0.6317357844944015,"score_spread":0.09066104550646703,"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."}}