{"id":"W4399296780","doi":"10.1101/2024.05.30.595956","title":"The genomic signature and transcriptional response of metal tolerance in brown trout inhabiting metal-polluted rivers","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts","funders":"","keywords":"Brown trout; Genomics; Trout; Biology; Population genomics; Zoology; Ecology; Fishery; Fish <Actinopterygii>; Genetics; Genome; Gene","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":[0.00009663605,0.0001502645,0.0002474173,0.0004203024,0.0002019147,0.000325095,0.0001030751,0.0002067321,0.0005292683],"category_scores_gemma":[0.0001871018,0.0001571645,0.0002188313,0.0003714557,0.000311968,0.0001030019,0.0003677048,0.0002156758,0.0001084381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002111748,"about_ca_system_score_gemma":0.0002093095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003047439,"about_ca_topic_score_gemma":0.00460239,"domain_scores_codex":[0.9998894,0.000009542023,0.000006839215,0.00005018331,0.00002116145,0.00002289641],"domain_scores_gemma":[0.9998389,0.00002212869,0.00006024818,0.000009290499,0.00003902701,0.00003049714],"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":[0.0003196881,0.00002657218,0.09473829,0.00003124221,0.000031287,0.00008639045,0.0003437232,0.0001836226,0.9025987,0.00005750856,0.00004341289,0.001539603],"study_design_scores_gemma":[0.000007014914,0.0001595585,0.989987,0.000003058277,0.00001976163,0.0001307031,0.0002939644,0.0003603969,0.008772687,0.00005178774,0.0002071571,0.000006958532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994531,0.00003717591,0.0001193653,0.000007270193,7.653962e-7,0.000003248862,0.0002591874,0.000004886734,0.0001151526],"genre_scores_gemma":[0.9980293,0.00005348865,0.0003188775,0.00003812071,0.000003170039,0.00001593801,0.0009167619,0.000004870761,0.0006194062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003047439,"threshold_uncertainty_score":0.006059408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186505820190262,"score_gpt":0.225543775306188,"score_spread":0.2136787171042853,"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."}}