{"id":"W2144486134","doi":"10.1093/toxsci/kfr220","title":"Predictive Models of Prenatal Developmental Toxicity from ToxCast High-Throughput Screening Data","year":2011,"lang":"en","type":"article","venue":"Toxicological Sciences","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":211,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"National Institutes of Health","keywords":"Developmental toxicity; Toxicity; Biology; In vivo; In vitro toxicology; High-throughput screening; Computational biology; Bioinformatics; Pharmacology; Internal medicine; Medicine; Genetics; Fetus","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":[0.003347405,0.001449715,0.0005662099,0.001417223,0.000282768,0.001078026,0.0006837753,0.0004420726,0.000840492],"category_scores_gemma":[0.004813998,0.0002593748,0.001448399,0.0009013437,0.0003759776,0.0004545256,0.000569805,0.0007792116,0.0003300873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218474,"about_ca_system_score_gemma":0.0010256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009646399,"about_ca_topic_score_gemma":0.007855744,"domain_scores_codex":[0.9990401,0.0003436587,0.00006301472,0.0002370543,0.0002409562,0.00007523003],"domain_scores_gemma":[0.9952284,0.003397207,0.0005548892,0.000310719,0.0004360476,0.00007274276],"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":[0.0006379345,0.000261357,0.0893779,0.0002035258,0.0003406158,0.0002388012,0.00006121219,0.8586449,0.01340814,0.001081913,0.001091172,0.03465249],"study_design_scores_gemma":[0.00001538264,0.000272063,0.0196234,0.00001268727,0.0001129114,0.00009719781,0.00002620486,0.9718533,0.005946312,0.001209731,0.0008133281,0.00001755565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8484418,0.0008778549,0.135976,0.0002540527,0.00002066422,0.0002224309,0.01051996,0.001704202,0.001983035],"genre_scores_gemma":[0.9660013,0.0003552135,0.02098042,0.0000593507,0.000007561457,0.0001740079,0.01156619,0.00004695341,0.0008090056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009646399,"threshold_uncertainty_score":0.01918048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1267336809513422,"score_gpt":0.3424834484130148,"score_spread":0.2157497674616726,"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."}}