{"id":"W1624362487","doi":"10.1007/s00239-015-9696-6","title":"Genomics of Adaptation to Multiple Concurrent Stresses: Insights from Comparative Transcriptomics of a Cichlid Fish from One of Earth’s Most Extreme Environments, the Hypersaline Soda Lake Magadi in Kenya, East Africa","year":2015,"lang":"en","type":"article","venue":"Journal of Molecular Evolution","topic":"Physiological and biochemical adaptations","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Alexander von Humboldt-Stiftung; Universität Konstanz; European Molecular Biology Organization","keywords":"Biology; Cichlid; Transcriptome; Extremophile; Extreme environment; Adaptation (eye); Tilapia; Gill; Freshwater fish; Zoology; Ecology; Gene; Fish <Actinopterygii>; Genetics; Fishery; Gene expression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001454895,0.0002052788,0.0002880644,0.0003889231,0.0008589022,0.0004731335,0.0002052651,0.0004205482,0.0005495845],"category_scores_gemma":[0.0001921639,0.000196577,0.0002159968,0.0005298475,0.0004983401,0.0002631997,0.0003467582,0.0004824895,0.0001361739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004955751,"about_ca_system_score_gemma":0.0005946213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02028996,"about_ca_topic_score_gemma":0.0358742,"domain_scores_codex":[0.9999233,0.000004284011,0.000003683273,0.00003280443,0.00001709548,0.00001884842],"domain_scores_gemma":[0.9998704,0.00002681014,0.00002994994,0.000007011948,0.00004402978,0.00002179137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002293939,0.00002830823,0.03579616,0.0000643474,0.00002459337,0.000398627,0.001362581,0.0002328162,0.9578771,0.000122638,0.00009668546,0.003766791],"study_design_scores_gemma":[0.000009429394,0.000144328,0.9846179,0.0000128453,0.00003327199,0.0004687148,0.001864833,0.0005083522,0.01091942,0.00008752512,0.001322158,0.00001111981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998973,0.0001079095,0.0001988996,0.00004580261,0.000002549427,0.000006132975,0.0002777893,0.000002173809,0.0003857452],"genre_scores_gemma":[0.9965335,0.0002422889,0.001031743,0.0001324155,0.000006721864,0.00002244582,0.0007952208,0.000007469012,0.001228102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02028996,"threshold_uncertainty_score":0.0403437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06277612110933566,"score_gpt":0.2215324341778244,"score_spread":0.1587563130684888,"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."}}