{"id":"W4290844484","doi":"10.1111/mec.16653","title":"Landscape genomics of the American lobster (<i>Homarus americanus</i>)","year":2022,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Homarus; American lobster; Biology; Genomics; Population genomics; Evolutionary biology; Ecology; Fishery; Computational biology; Genetics; Genome; Crustacean; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00008760511,0.00008022322,0.0001035212,0.0005076748,0.0001803839,0.0002765194,0.0000900018,0.0001056453,0.0006076504],"category_scores_gemma":[0.0001514605,0.00005316616,0.00009467427,0.000423626,0.0002008291,0.0001251689,0.0001818578,0.0001297612,0.0000826121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002284261,"about_ca_system_score_gemma":0.000143787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01444911,"about_ca_topic_score_gemma":0.03518736,"domain_scores_codex":[0.999956,0.00000852805,0.000001883579,0.00001782203,0.000005579539,0.00001009352],"domain_scores_gemma":[0.9999062,0.00002010647,0.00003855183,0.000006466128,0.00001428231,0.00001443967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002401317,0.00004194849,0.7651628,0.00006501919,0.0001092111,0.0001877532,0.000712434,0.00115384,0.202993,0.000304053,0.0001681438,0.02886174],"study_design_scores_gemma":[0.000001300224,0.00001636902,0.9984666,0.000002943448,0.00001193811,0.00006167409,0.0001686077,0.0003014395,0.0007145265,0.00004917106,0.0002035726,0.000001907158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993737,0.00005081551,0.0002379646,0.000009377181,2.984297e-7,0.000001198969,0.0001018555,0.000003343007,0.0002215243],"genre_scores_gemma":[0.999347,0.0000421806,0.000281058,0.00001313076,6.906645e-7,0.000002653753,0.0001475117,0.000002503811,0.0001631716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01444911,"threshold_uncertainty_score":0.02873003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005894931586236694,"score_gpt":0.1880599997997885,"score_spread":0.1821650682135518,"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."}}