{"id":"W1975155217","doi":"10.1007/s10126-010-9285-z","title":"An Integrated Approach to Gene Discovery and Marker Development in Atlantic Cod (Gadus morhua)","year":2010,"lang":"en","type":"article","venue":"Marine Biotechnology","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Memorial University of Newfoundland; Université Sainte-Anne; Institute for Marine Biosciences","funders":"Division of Ocean Sciences; Genome Canada; Fisheries and Oceans Canada; Genome Atlantic; Atlantic Canada Opportunities Agency; McGill University","keywords":"Biology; Atlantic cod; Gadus; Genomics; Domestication; Aquaculture; Selective breeding; Biotechnology; Computational biology; Gene; Fishery; Molecular marker; Molecular breeding; Genetics; Genome; Evolutionary biology; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000196453,0.0002720668,0.0003162597,0.0003939733,0.0001006759,0.00003746566,0.0003963689,0.0006376731,0.0001251465],"category_scores_gemma":[0.00004775813,0.0002273617,0.00003128272,0.0003417672,0.0002474372,0.00009987518,0.0005671158,0.0006067092,0.0001883461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003592806,"about_ca_system_score_gemma":0.00004343521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000291758,"about_ca_topic_score_gemma":0.001047634,"domain_scores_codex":[0.9985776,0.00005594816,0.0002870164,0.0005938471,0.00002559964,0.0004599775],"domain_scores_gemma":[0.999414,0.00001445664,0.00005904206,0.0004442164,0.00002830364,0.00004002295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002677253,0.0004750764,0.03966462,0.00002476711,0.0001101596,0.00002027958,0.0001531506,0.000001398247,0.9304339,0.005055567,0.001345983,0.02244736],"study_design_scores_gemma":[0.002753281,0.0002357956,0.3215271,0.00002215267,0.00007025864,0.0002185277,0.0005656168,0.0000326094,0.2417943,0.0001717364,0.4316939,0.0009147899],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964518,0.00009626512,0.001084383,0.0006166118,0.0002885979,0.0004799985,0.0000131761,0.0001912346,0.0007779095],"genre_scores_gemma":[0.991232,0.0000285165,0.005113506,0.0002211874,0.00001546502,0.00006063095,0.001018879,0.0000231226,0.002286643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6886396,"threshold_uncertainty_score":0.9271541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005168418186707655,"score_gpt":0.2010965877635443,"score_spread":0.1959281695768367,"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."}}