{"id":"W4288795470","doi":"","title":"Representing Foods Potentially Involved in Food-Drug Interactions using FoodOn (FIDEO)","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Biochemical Analysis and Sensing Techniques","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Drug; Computer science; Medicine; Pharmacology","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":[],"consensus_categories":[],"category_scores_codex":[0.00061266,0.0008638794,0.0003525656,0.001479729,0.0005936516,0.001224524,0.0003869233,0.001014687,0.02607058],"category_scores_gemma":[0.001046483,0.0001748854,0.0005696325,0.001316043,0.0003083422,0.0007683321,0.0008554812,0.0003205002,0.004045806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004664561,"about_ca_system_score_gemma":0.0005106053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001921407,"about_ca_topic_score_gemma":0.003240604,"domain_scores_codex":[0.9997709,0.00005308229,0.00001067126,0.00005299746,0.00006501303,0.00004733179],"domain_scores_gemma":[0.9996253,0.0001409302,0.00005159585,0.00004390131,0.00008541771,0.00005273007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002835756,0.000291514,0.01374631,0.001651125,0.00006799038,0.002124204,0.0008682898,0.004301501,0.4273586,0.01620364,0.03154664,0.4990044],"study_design_scores_gemma":[0.0001404424,0.001642185,0.03729718,0.0004692203,0.000253786,0.005452613,0.001476155,0.02993088,0.3578271,0.01630923,0.5489565,0.0002447008],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"software","genre_scores_codex":[0.625872,0.005123626,0.1892326,0.001888886,0.001048489,0.0007807445,0.01852577,0.008114844,0.1494131],"genre_scores_gemma":[0.4922016,0.003296757,0.4077201,0.0009370747,0.0001061236,0.0005040888,0.01158645,0.0006536173,0.08299402],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02607058,"threshold_uncertainty_score":0.08721471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0383897163556433,"score_gpt":0.2746596258223566,"score_spread":0.2362699094667133,"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."}}