{"id":"W4377092805","doi":"10.1002/etc.5676","title":"Development and Initial Testing of EcoToxChip, a Novel Toxicogenomics Tool for Environmental Management and Chemical Risk Assessment","year":2023,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; McGill University; Environment and Climate Change Canada","funders":"Genome Prairie; Environment and Climate Change Canada; University of Saskatchewan; Genome Canada; McGill University","keywords":"Toxicogenomics; Pimephales promelas; Biology; Toxicology; Computational biology; Biochemical engineering; Risk analysis (engineering); Computer science; Minnow; Fish <Actinopterygii>; Engineering; Gene expression; Genetics; Gene; Medicine; Fishery","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003749456,0.0007729425,0.0004053608,0.0007261217,0.0004157995,0.0008693389,0.0008891256,0.0005892051,0.002048689],"category_scores_gemma":[0.002285761,0.0003422347,0.0004372838,0.0003105726,0.000697525,0.0007418621,0.0009821544,0.0007552181,0.0008072747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004824671,"about_ca_system_score_gemma":0.0009949437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008190372,"about_ca_topic_score_gemma":0.00275615,"domain_scores_codex":[0.9980614,0.0004261,0.00009450444,0.0004334528,0.0008664982,0.0001181482],"domain_scores_gemma":[0.9982294,0.0004385127,0.0002262138,0.0002480632,0.0007025963,0.0001552314],"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":[0.0000819667,0.00006140263,0.003430643,0.0001161713,0.00002450489,0.00005834312,0.00006775269,0.0009919651,0.9708793,0.0006498614,0.0004095623,0.02322842],"study_design_scores_gemma":[0.00001542096,0.0008080566,0.009135618,0.0000253696,0.00005444941,0.0002613804,0.00008493623,0.007671279,0.9638022,0.0004240551,0.01767615,0.0000409975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3122724,0.001265706,0.6685765,0.0007453432,0.0001533937,0.002437251,0.004068108,0.003260458,0.007220783],"genre_scores_gemma":[0.2645087,0.00123938,0.7150523,0.0007400977,0.00005428211,0.003186094,0.004657284,0.0005067803,0.01005517],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003749456,"threshold_uncertainty_score":0.01982927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01421349428469571,"score_gpt":0.2338536725777456,"score_spread":0.2196401782930499,"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."}}