{"id":"W2981124990","doi":"","title":"Développement d'outils bio-informatiques pour l'analyse de données épigénomiques avec référence externe et pour l’évaluation du nombre de couples à risque à partir de fichiers de variants génétiques","year":2018,"lang":"fr","type":"article","venue":"Knowledge UdeS (Institutional Deposit of the University of Sherbrooke)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; McGill University; Génome Québec; Fonds de Recherche du Québec - Santé; Compute Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Humanities; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001115248,0.0002771491,0.0003280268,0.000103213,0.0004539987,0.00004380534,0.0007254058,0.0004738497,0.00005321915],"category_scores_gemma":[0.0004264134,0.000268389,0.0002731448,0.0001624797,0.002152755,0.00004780594,0.0003777772,0.0002183989,0.00001539784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067781,"about_ca_system_score_gemma":0.001975708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001697175,"about_ca_topic_score_gemma":0.009205885,"domain_scores_codex":[0.9981703,0.0004580142,0.0003793447,0.000315784,0.000207489,0.0004691249],"domain_scores_gemma":[0.9988078,0.00009005349,0.0002343005,0.0003184951,0.0003550612,0.0001942798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007787823,0.001153959,0.1413597,0.002615603,0.001199053,0.00004009372,0.04352557,0.006150427,0.75661,0.005405186,0.01243723,0.02872439],"study_design_scores_gemma":[0.0009824545,0.000377084,0.2342622,0.002510323,0.0004244171,0.0001110067,0.001214473,0.06870098,0.6778553,0.001408726,0.01178968,0.0003634208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7214456,0.005554645,0.2683503,0.002420101,0.0001543548,0.0001445263,0.0000431107,0.00002380484,0.001863535],"genre_scores_gemma":[0.9179864,0.007227915,0.07345405,0.0001856194,0.0001913723,0.000001975545,0.00003267061,0.00001148963,0.0009084918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1965408,"threshold_uncertainty_score":0.9999768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02540410022622588,"score_gpt":0.2554489353208231,"score_spread":0.2300448350945972,"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."}}