{"id":"W3154676607","doi":"10.12688/wellcomeopenres.16718.1","title":"An automated approach to identify scientific publications reporting pharmacokinetic parameters","year":2021,"lang":"en","type":"preprint","venue":"Wellcome Open Research","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre","funders":"Medical Research Council; National Institute for Health and Care Research; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; Alan Turing Institute; University College London; Great Ormond Street Hospital for Children; Wellcome Trust","keywords":"Computer science; Pipeline (software); Pooling; Information retrieval; Set (abstract data type); Data mining; Machine learning; Data science; Artificial intelligence","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","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.006865618,0.00169119,0.001244442,0.04348459,0.00139959,0.00462129,0.002028459,0.001482276,0.008766329],"category_scores_gemma":[0.03483146,0.0005560176,0.002058372,0.016862,0.0006070909,0.004236529,0.003095012,0.001199446,0.01096203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001309236,"about_ca_system_score_gemma":0.00638332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002660681,"about_ca_topic_score_gemma":0.003904834,"domain_scores_codex":[0.9937697,0.001127243,0.001186845,0.001559372,0.00199208,0.0003646749],"domain_scores_gemma":[0.9681327,0.01240059,0.005338374,0.003400345,0.00971509,0.001012726],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007484546,0.0002961213,0.02128318,0.008518994,0.0003623814,0.001394696,0.0006420822,0.003956215,0.01863774,0.005337226,0.08802515,0.8507978],"study_design_scores_gemma":[0.0004090014,0.00103738,0.07617289,0.00371217,0.001912241,0.005093058,0.002012732,0.1215046,0.07362662,0.03399539,0.6800012,0.0005226934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1176172,0.02746164,0.4266322,0.005693109,0.002506956,0.006346512,0.2871045,0.08754175,0.03909617],"genre_scores_gemma":[0.1364314,0.004800713,0.6455863,0.0004506912,0.0008093431,0.002331689,0.1999039,0.001243671,0.008442228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9931344,"threshold_uncertainty_score":0.0363093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.417953394708161,"score_gpt":0.5600628459605473,"score_spread":0.1421094512523863,"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."}}