{"id":"W3134842774","doi":"10.5281/zenodo.4650697","title":"FIDEO: Food Interactions with Drugs Evidence Ontology","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"Horizon 2020 Framework Programme; Agence Nationale de la Recherche; European Commission","keywords":"Ontology; Computer science; Data science; Epistemology; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001148653,0.0002815122,0.0003087878,0.00006578272,0.0001756676,0.000126327,0.000939353,0.0003486167,0.00006101498],"category_scores_gemma":[0.00230884,0.0002578404,0.0001535189,0.0001549487,0.0004079865,0.000006668479,0.001254201,0.0006051414,0.00002396929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003650185,"about_ca_system_score_gemma":0.0003548828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003382746,"about_ca_topic_score_gemma":0.002582341,"domain_scores_codex":[0.9964129,0.001922566,0.0003284398,0.0008250709,0.0002288901,0.0002820957],"domain_scores_gemma":[0.9967698,0.0005535972,0.0003143097,0.001353875,0.0008267828,0.0001815656],"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":[0.0009117611,0.00266788,0.01653644,0.00175813,0.002691973,0.00007136812,0.03642692,0.0001875546,0.2013886,0.03382181,0.07748362,0.626054],"study_design_scores_gemma":[0.002068092,0.00004103881,0.01163015,0.007959321,0.0003567236,0.0001575045,0.001474618,0.00373346,0.4179972,0.005385217,0.5469429,0.002253862],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5025883,0.008919114,0.3657238,0.08814833,0.0006855903,0.0007452401,0.0001536582,0.0003865189,0.03264937],"genre_scores_gemma":[0.9503379,0.0006905096,0.04457632,0.0003868918,0.00006549055,0.00008641383,0.0004121811,0.00003447904,0.003409829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6238001,"threshold_uncertainty_score":0.9999874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02800496591158324,"score_gpt":0.2679909560429179,"score_spread":0.2399859901313347,"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."}}