{"id":"W2473743914","doi":"10.1021/acs.est.6b01249","title":"Combined Transcriptomic and Proteomic Approach to Identify Toxicity Pathways in Early Life Stages of Japanese Medaka (<i>Oryzias latipes</i>) Exposed to 1,2,5,6-Tetrabromocyclooctane (TBCO)","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"State Administration of Foreign Experts Affairs; Chinese Academy of Sciences; Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Oryzias; Toxicity; Computational biology; Transcriptome; Biology; Fish <Actinopterygii>; Chemistry; Biochemistry; Gene; Fishery; Gene expression","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":[0.0001162706,0.0005136436,0.0005651407,0.0004846963,0.000357892,0.0003537442,0.0002230526,0.0003653547,0.0005346666],"category_scores_gemma":[0.0001073822,0.0002308027,0.0005760877,0.0004434211,0.0002166455,0.0004515509,0.0004915923,0.0006029662,0.0002128524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002768684,"about_ca_system_score_gemma":0.0003817253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001858762,"about_ca_topic_score_gemma":0.004321279,"domain_scores_codex":[0.9999038,0.00000455806,0.000005088191,0.00004733175,0.00002241855,0.00001673905],"domain_scores_gemma":[0.9999204,0.000007111248,0.00002230502,0.000004584423,0.00002906289,0.00001651908],"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":[0.00009574171,0.00001685446,0.003239159,0.000188483,0.00002841589,0.00006061901,0.00005363586,0.00008647704,0.9937874,0.00004776431,0.0001232493,0.002272259],"study_design_scores_gemma":[0.00003500509,0.0009788465,0.6167409,0.00009229759,0.0006290507,0.0009201644,0.00121632,0.008073597,0.3588057,0.0006224402,0.01179562,0.00009002652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748626,0.006046072,0.009463292,0.0002254324,0.00009169066,0.0001065378,0.007582414,0.0001889656,0.001432941],"genre_scores_gemma":[0.9467069,0.00591194,0.02583607,0.0006907122,0.00006141121,0.0004137483,0.0137946,0.0001034815,0.006481068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001858762,"threshold_uncertainty_score":0.003695905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170054294706381,"score_gpt":0.2202825834345425,"score_spread":0.2085820404874787,"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."}}