{"id":"W6950680199","doi":"10.5683/sp3/mr77ht","title":"What did the scientific literature learn from internal company documents in the pharmaceutical industry: A scoping review dataset","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Pharmaceutical industry; Scientific literature; Public sector; Systematic review; Sociology of scientific knowledge; Public opinion; Corporate governance","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"],"consensus_categories":[],"category_scores_codex":[0.01595762,0.001615394,0.002862829,0.0424149,0.001865361,0.004835388,0.002358826,0.003512678,0.02604109],"category_scores_gemma":[0.122095,0.001287361,0.003076803,0.03659487,0.001154289,0.002546795,0.004663029,0.002174272,0.01028505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005064444,"about_ca_system_score_gemma":0.01200473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02082869,"about_ca_topic_score_gemma":0.04733996,"domain_scores_codex":[0.9780961,0.005932084,0.009134589,0.00193272,0.004056445,0.000848071],"domain_scores_gemma":[0.8647653,0.09888454,0.0138825,0.005846675,0.01519265,0.001428328],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001008963,0.0001631664,0.01204701,0.2922103,0.001975577,0.0006885705,0.002341722,0.001410075,0.001695051,0.006016109,0.6188047,0.06163868],"study_design_scores_gemma":[0.0008321697,0.0000956616,0.01583513,0.07792446,0.00164346,0.0004169029,0.001203547,0.0004373111,0.001046665,0.001964513,0.8984761,0.0001240503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001621607,0.00558723,0.0005511554,0.0005891618,0.00005593072,0.0005553893,0.9883878,0.000161197,0.002490576],"genre_scores_gemma":[0.007536212,0.00668077,0.00517311,0.0007446905,0.00004990153,0.006951969,0.9711704,0.0001534618,0.001539526],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9840424,"threshold_uncertainty_score":0.08711612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07110715261015693,"score_gpt":0.4027442861706116,"score_spread":0.3316371335604547,"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."}}