{"id":"W2508113278","doi":"","title":"Restoring the Integrity of the Pharmaceutical Science Record: Two Tales of Transparency","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Pharmaceutical industry and healthcare","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transparency (behavior); Language change; Public relations; Scientific misconduct; Political science; Scientific evidence; Promotion (chess); Overconsumption; Medical prescription; Misconduct; Pharmaceutical marketing; Internet privacy; Law; Medicine; Alternative medicine; Computer science; Economics; Pharmacology; Pharmaceutical industry","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":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.08044129,0.0006326067,0.001262124,0.005331856,0.01293135,0.04652434,0.003678783,0.02326134,0.005325864],"category_scores_gemma":[0.2460855,0.00100529,0.001525737,0.004394093,0.06005004,0.05049071,0.0168501,0.03370008,0.001981272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009837656,"about_ca_system_score_gemma":0.02516299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002976382,"about_ca_topic_score_gemma":0.002685281,"domain_scores_codex":[0.8609872,0.07296041,0.0068677,0.004560467,0.04899578,0.005628462],"domain_scores_gemma":[0.5644165,0.3291701,0.02208746,0.04625757,0.02951171,0.008556569],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005130091,0.00005149802,0.0006054034,0.0003425393,0.00004164451,0.0005852672,0.01361345,0.0003495337,0.0003513302,0.8698016,0.06250287,0.05170361],"study_design_scores_gemma":[0.00005582065,0.00006315207,0.0007061088,0.001425819,0.00004050901,0.0007885879,0.007076974,0.00071966,0.001448804,0.6475508,0.3399732,0.0001504745],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004180422,0.009885116,0.01542737,0.9138801,0.004080861,0.00005361756,0.00004657033,0.000113118,0.05233285],"genre_scores_gemma":[0.5989873,0.03760733,0.04407953,0.2413144,0.02798863,0.0003246017,0.0001501947,0.0007203729,0.04882758],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9767386,"threshold_uncertainty_score":0.4254193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3540028130539468,"score_gpt":0.5459519881410382,"score_spread":0.1919491750870914,"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."}}