{"id":"W4313399235","doi":"10.1016/j.ecoenv.2022.114466","title":"Toxicogenomics scoring system: TGSS, a novel integrated risk assessment model for chemical carcinogenicity prediction","year":2022,"lang":"en","type":"article","venue":"Ecotoxicology and Environmental Safety","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Fundamental Research Funds for the Central Universities; Chinese Academy of Meteorological Sciences; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Toxicogenomics; Risk assessment; Computational biology; Molecular biomarkers; Carcinogenesis; Carcinogen; Biology; Gene; Bioinformatics; Toxicology; Gene expression; Oncology; Genetics; Computer science; 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":[],"consensus_categories":[],"category_scores_codex":[0.001586933,0.001414093,0.0008739458,0.002350962,0.0003961156,0.001137067,0.0009620466,0.0008937901,0.001742717],"category_scores_gemma":[0.003614548,0.0002742535,0.001412311,0.000945157,0.0004033585,0.0007958406,0.0008645551,0.00077297,0.0003189852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001106681,"about_ca_system_score_gemma":0.002079903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01046049,"about_ca_topic_score_gemma":0.008599349,"domain_scores_codex":[0.999375,0.0001858583,0.0000632416,0.0001381168,0.0001829646,0.00005481337],"domain_scores_gemma":[0.9989142,0.000539058,0.0001468001,0.0000657046,0.0002658928,0.00006822014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002643909,0.0001923582,0.03001131,0.0001823362,0.0003533187,0.0001804219,0.00005188946,0.8619331,0.003268924,0.003011242,0.003641218,0.09690958],"study_design_scores_gemma":[0.00001136567,0.00006957575,0.001395982,0.00001088174,0.00004417176,0.00003841305,0.000007838022,0.9947714,0.0004689948,0.002770148,0.0003993295,0.00001192676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1429065,0.0007938883,0.846269,0.00101601,0.00009998489,0.0004037353,0.002815291,0.003059998,0.002635692],"genre_scores_gemma":[0.8435087,0.0004055983,0.1504398,0.0003259195,0.00008221358,0.000494608,0.003325641,0.00008550956,0.001331927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01046049,"threshold_uncertainty_score":0.02079922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487631304947507,"score_gpt":0.2365482284940344,"score_spread":0.2216719154445593,"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."}}