{"id":"W2604849910","doi":"10.1007/s11356-017-8977-6","title":"Fishing for contaminants: identification of three mechanism specific transcriptome signatures using Danio rerio embryos","year":2017,"lang":"en","type":"article","venue":"Environmental Science and Pollution Research","topic":"Animal Genetics and Reproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Bundesministerium für Bildung und Forschung","keywords":"Danio; Ecotoxicology; Transcriptome; Zebrafish; Identification (biology); Embryo; Mechanism (biology); Biology; Computational biology; Cell biology; Toxicology; Genetics; Ecology; Gene; Gene expression","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":[],"consensus_categories":[],"category_scores_codex":[0.001632542,0.00006298444,0.00006496168,0.00006379294,0.001114312,0.0001042474,0.0002747567,0.00006906804,0.000006776155],"category_scores_gemma":[0.00008233846,0.00005744517,0.00002850007,0.00005010839,0.001015127,0.00002827801,0.0001277701,0.00006929738,0.000001123574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004368679,"about_ca_system_score_gemma":0.00004463079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004932729,"about_ca_topic_score_gemma":0.00001384306,"domain_scores_codex":[0.998872,0.00002689746,0.000139604,0.000372721,0.0003722068,0.0002165417],"domain_scores_gemma":[0.9994796,0.000003627197,0.00008910405,0.0003248632,0.00004630386,0.00005652531],"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":[0.00004351336,0.00002594965,0.0003619364,0.000007160225,0.00000382529,1.785371e-7,0.00005741902,0.00001491933,0.9963377,0.0003741945,0.0000578078,0.002715427],"study_design_scores_gemma":[0.0002013052,0.0002294754,0.0953173,0.000008458292,0.000004090703,0.000003639995,0.00026623,0.0007019613,0.8995234,0.000414893,0.003253263,0.00007596869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947435,0.0004992352,0.003930025,0.0002769349,0.0001458737,0.0003128241,0.00003591986,0.000001509626,0.00005416196],"genre_scores_gemma":[0.9987391,0.0004868393,0.0003617828,0.000008811271,0.0001268833,0.000009952539,0.000008445577,0.000006479255,0.0002516943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09681425,"threshold_uncertainty_score":0.8570496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0595169453119393,"score_gpt":0.3375479595566772,"score_spread":0.2780310142447379,"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."}}