{"id":"W2113592430","doi":"10.1111/faf.12007","title":"Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management","year":2012,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry","funders":"European Social Fund; International Council for the Exploration of the Sea; Bergens Forskningsstiftelse; Vienna Science and Technology Fund; Leibniz-Gemeinschaft; Bundesministerium für Wissenschaft und Forschung; Norges Forskningsråd; Department for Environment, Food and Rural Affairs, UK Government; Austrian Science Fund; European Science Foundation; European Commission","keywords":"Fishing; Fishery; Fisheries management; Ecosystem-based management; Fisheries science; Ecosystem; Ecosystem approach; Business; Environmental resource management; Ecology; Economics; Biology","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":[0.0005842743,0.0002118702,0.0002988835,0.000105755,0.0002318229,0.0001141444,0.0002987172,0.00009870678,0.000838162],"category_scores_gemma":[0.00006085372,0.000195221,0.0000688439,0.0003638758,0.0002691132,0.001940901,0.0004023728,0.0001405988,0.000003269916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002175,"about_ca_system_score_gemma":0.00002708812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007223834,"about_ca_topic_score_gemma":0.0003377141,"domain_scores_codex":[0.9981557,0.00009304573,0.0003836589,0.0003718994,0.0003747474,0.0006209832],"domain_scores_gemma":[0.9992965,0.0001029358,0.0001010454,0.0002603833,0.00002900185,0.0002100677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009388551,0.0001753998,0.9761813,0.0001811772,0.00002280913,0.000001525676,0.0009039092,0.00005413523,0.0001036231,0.0003253598,0.01746162,0.004495204],"study_design_scores_gemma":[0.0003158443,0.000200951,0.9450456,0.00002114764,0.00001191573,0.00001384196,0.002493296,0.001494825,0.00002365021,0.0003697459,0.04974969,0.0002594895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8552899,0.00002949031,0.0005155819,0.0005735309,0.0001190412,0.0008409659,0.0001483913,0.00003828479,0.1424449],"genre_scores_gemma":[0.9832181,0.00003418509,0.01557017,0.0001973914,0.00009589407,0.0003079817,0.0001160348,0.00002126234,0.0004389835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1420059,"threshold_uncertainty_score":0.9177286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02800310948945779,"score_gpt":0.2799060540015923,"score_spread":0.2519029445121345,"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."}}