{"id":"W4405934475","doi":"10.2196/55277","title":"Creation of Scientific Response Documents for Addressing Product Medical Information Inquiries: Mixed Method Approach Using Artificial Intelligence","year":2024,"lang":"en","type":"article","venue":"JMIR AI","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pfizer (Canada)","funders":"","keywords":"Preprint; Product (mathematics); Data science; Pharmaceutical industry; Computer science; Business; World Wide Web; Medicine","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":[0.2037963,0.002600614,0.002480066,0.01301179,0.004061866,0.009418691,0.006506886,0.003295638,0.01155362],"category_scores_gemma":[0.363469,0.002520787,0.003561494,0.009136298,0.002697691,0.006212263,0.008782143,0.003414031,0.003023251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006904329,"about_ca_system_score_gemma":0.01220808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004631098,"about_ca_topic_score_gemma":0.007775874,"domain_scores_codex":[0.7187058,0.2425778,0.01539461,0.01006334,0.0120797,0.001178809],"domain_scores_gemma":[0.3427332,0.5727326,0.02723655,0.02234714,0.03313208,0.001818572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004292073,0.004604967,0.02090709,0.01874411,0.001714403,0.0006420361,0.07038901,0.00584955,0.006216813,0.02097736,0.007059176,0.8386034],"study_design_scores_gemma":[0.01066558,0.0158632,0.06884232,0.0172777,0.006375329,0.002056511,0.1233266,0.3565165,0.06299277,0.1617177,0.172015,0.002350825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08052166,0.002054574,0.8090539,0.002047429,0.000257501,0.09260872,0.002617089,0.001818468,0.009020653],"genre_scores_gemma":[0.08368666,0.0004099836,0.8495392,0.0007214342,0.0000734612,0.06303244,0.000796741,0.0001773163,0.001562875],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2037963,"threshold_uncertainty_score":0.9818609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08223819874697301,"score_gpt":0.4333640955664769,"score_spread":0.3511258968195039,"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."}}