{"id":"W2261793788","doi":"","title":"Opportunities to integrate new approaches in genetic toxicology: An ILSI-HESI workshop report","year":2014,"lang":"en","type":"article","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Risk assessment; Toxicogenomics; Computational biology; Risk analysis (engineering); Toxicology; Biology; Engineering ethics; Computer science; Medicine; Genetics; Engineering; Gene","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","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0005078312,0.0004763649,0.001012627,0.002279016,0.0001164763,0.00001847877,0.0006977026,0.006245219,0.0000452433],"category_scores_gemma":[0.0009649207,0.0004184998,0.0001515844,0.001423022,0.001140857,0.0002158993,0.0002828326,0.003316067,0.00003384517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001422173,"about_ca_system_score_gemma":0.0004318855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000723265,"about_ca_topic_score_gemma":0.0006593345,"domain_scores_codex":[0.9972051,0.00005821749,0.0008702022,0.0008807748,0.0002718067,0.0007138452],"domain_scores_gemma":[0.9975653,0.00003856057,0.0003224653,0.001646078,0.0001076954,0.0003198883],"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":[0.001015241,0.00236377,0.08156451,0.0005061517,0.001199474,0.008438211,0.002149021,0.0008097465,0.0240401,0.1543998,0.01827055,0.7052435],"study_design_scores_gemma":[0.00566837,0.003575414,0.0272672,0.002109202,0.0006446601,0.005874612,0.003083522,0.001381577,0.06545283,0.01109384,0.8720486,0.001800237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.764535,0.001108256,0.008162028,0.216977,0.0007833091,0.0009758911,0.000008447083,0.0009336778,0.006516431],"genre_scores_gemma":[0.9395552,0.0005818349,0.05344677,0.001241912,0.0001301647,0.00008965148,0.00004967634,0.0000615334,0.004843222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.853778,"threshold_uncertainty_score":0.9998267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.069485724539569,"score_gpt":0.2845675793770299,"score_spread":0.2150818548374609,"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."}}