{"id":"W2974585411","doi":"10.1101/772319","title":"Life out of water: Genomic and physiological mechanisms underlying skin phenotypic plasticity","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neurobiology and Insect Physiology Research","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; National Science Foundation","keywords":"Biology; Phenotypic plasticity; Adaptation (eye); Ecology; Vertebrate; Evolutionary biology; Neuroscience; Genetics; Gene","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":[0.00010979,0.0001624897,0.000184684,0.0003878771,0.0001928662,0.0002357682,0.0002149664,0.000265536,0.001658611],"category_scores_gemma":[0.0002093423,0.0001278243,0.0001578606,0.0001954882,0.0003164318,0.0001860534,0.0003817485,0.0002913839,0.0001650415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001471816,"about_ca_system_score_gemma":0.00006874674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004369848,"about_ca_topic_score_gemma":0.00061242,"domain_scores_codex":[0.999878,0.00001621293,0.000007029852,0.00005080669,0.00001831853,0.00002953148],"domain_scores_gemma":[0.9998116,0.00002522765,0.00008095423,0.00002241574,0.00002101522,0.00003888511],"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":[0.00007549335,0.000009862151,0.006866941,0.00001725564,0.000008581175,0.0001229706,0.00006467265,0.00004677905,0.9908125,0.0001027432,0.00002691726,0.001845251],"study_design_scores_gemma":[0.000007510745,0.0001157218,0.9383442,0.000007125251,0.0000213151,0.0006058791,0.0002243808,0.0006502987,0.05911461,0.0002183235,0.0006767955,0.00001386548],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983643,0.0001225954,0.0008666025,0.00003503411,0.000003773061,0.000003752363,0.0001693361,0.00002293876,0.0004116257],"genre_scores_gemma":[0.9991224,0.00003152143,0.00027946,0.00003105597,0.000002940117,0.000007283566,0.0001374541,0.000007453106,0.0003803648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001658611,"threshold_uncertainty_score":0.005548656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06062849236168132,"score_gpt":0.2684142313457345,"score_spread":0.2077857389840532,"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."}}