{"id":"W2963828809","doi":"10.1101/708974","title":"Evolved for success in novel environments: The round goby genome","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Deutsche Forschungsgemeinschaft; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Freiwillige Akademische Gesellschaft; Grantová Agentura České Republiky; Univerzita Karlova v Praze; Vetenskapsrådet; National Science Foundation","keywords":"Biology; Ecology; Evolutionary biology; Neogobius; Round goby; Adaptation (eye); Habitat; Goby; Genome; Gene; Invasive species; Fish <Actinopterygii>; Fishery; Genetics; Neuroscience","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":[0.0001596659,0.0002663892,0.0003129838,0.0007372585,0.0005205607,0.0005887549,0.0002355512,0.000459747,0.001961869],"category_scores_gemma":[0.0004069273,0.0001901854,0.0003460698,0.0009821909,0.0002419738,0.0003828048,0.0006328123,0.0007754014,0.0004560487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003498374,"about_ca_system_score_gemma":0.0003626457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002302144,"about_ca_topic_score_gemma":0.008552878,"domain_scores_codex":[0.9999222,0.000006249262,0.000003304739,0.00003556587,0.00001541268,0.00001736033],"domain_scores_gemma":[0.9998031,0.00006559282,0.00004942992,0.00001536227,0.00002158328,0.00004494765],"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":[0.0006291459,0.00004565861,0.03653754,0.000386443,0.000187097,0.001859306,0.0009783361,0.001087553,0.9299003,0.001045264,0.002363509,0.02497973],"study_design_scores_gemma":[0.00004986329,0.0002513507,0.8779569,0.0002212623,0.0004451736,0.002991796,0.001585867,0.008599138,0.0442121,0.002184176,0.06141112,0.00009133886],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869261,0.001258274,0.003486189,0.0003372743,0.00003594358,0.00001691471,0.006348598,0.0002829445,0.001307764],"genre_scores_gemma":[0.939983,0.001028218,0.01994901,0.0003852773,0.00003326646,0.00004819408,0.03501372,0.0003696728,0.003189737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002302144,"threshold_uncertainty_score":0.006563067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01251365780320043,"score_gpt":0.2095020772434499,"score_spread":0.1969884194402494,"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."}}