{"id":"W1892712685","doi":"10.1093/biosci/biv068","title":"Assessing Ecological and Evolutionary Consequences of Growth-Accelerated Genetically Engineered Fishes","year":2015,"lang":"en","type":"article","venue":"BioScience","topic":"Animal Genetics and Reproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Vetenskapsrådet","keywords":"Transgenesis; Adaptation (eye); Biology; Fish <Actinopterygii>; Ecology; Genetically modified organism; Growth hormone; Biotechnology; Fishery; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001748746,0.00006617403,0.00007164449,0.00002205974,0.000048583,0.00002642958,0.00009818779,0.00007361116,0.000003555293],"category_scores_gemma":[0.0002707885,0.00005290721,0.00001653569,0.0001075186,0.0005315683,0.000006753869,0.00007510964,0.00002859767,8.780835e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005856362,"about_ca_system_score_gemma":0.000129544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000880257,"about_ca_topic_score_gemma":0.000001010921,"domain_scores_codex":[0.9993595,0.00002882896,0.0001196482,0.0002663364,0.0001080201,0.0001176541],"domain_scores_gemma":[0.9996078,0.000005872965,0.00004329528,0.00009656155,0.0001664427,0.00008004803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009936204,0.00002884884,0.005685981,0.000004146616,0.000003001797,8.8242e-7,0.00001302951,0.00004042804,0.9935011,0.0001455477,0.0001923285,0.0003747969],"study_design_scores_gemma":[0.0002012492,0.0006667604,0.2216358,0.000007402159,0.000008081447,0.00005757582,0.0001861803,0.0004396434,0.7741832,0.000442387,0.002012055,0.0001596791],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973162,0.000993725,0.0007740565,0.0002386023,0.0001231127,0.00005929285,0.000002998641,0.000006784431,0.0004852179],"genre_scores_gemma":[0.9939556,0.0001607836,0.005696977,0.00004991734,0.00006662458,0.000002848941,0.00000546261,0.000002726726,0.00005911983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2193179,"threshold_uncertainty_score":0.2157493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05153144689534447,"score_gpt":0.2843373399569686,"score_spread":0.2328058930616241,"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."}}