{"id":"W4383506603","doi":"10.1111/faf.12774","title":"Life in the fast lane: Revisiting the fast growth—High survival paradigm during the early life stages of fishes","year":2023,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Victoria; Fisheries and Oceans Canada; Université du Québec à Chicoutimi; Université du Québec à Rimouski","funders":"Japan Society for the Promotion of Science; Japan Fisheries Research and Education Agency","keywords":"Biology; Predation; Population; Population growth; Larva; Selection (genetic algorithm); Growth rate; Demography; Ecology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0145792,0.000391075,0.0005848932,0.002041754,0.001249063,0.002263789,0.002926309,0.001188135,0.001770845],"category_scores_gemma":[0.01391348,0.0002409815,0.0007975753,0.001182072,0.007784392,0.004230796,0.002982409,0.002851375,0.0003142174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002319059,"about_ca_system_score_gemma":0.002671881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009102912,"about_ca_topic_score_gemma":0.01293584,"domain_scores_codex":[0.9966313,0.002040401,0.000199968,0.0006512044,0.000321173,0.0001560055],"domain_scores_gemma":[0.9899784,0.005630659,0.001528667,0.0007111731,0.001381953,0.0007691705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0006781114,0.0002604418,0.356877,0.002072931,0.0004728864,0.002562498,0.01355913,0.02746719,0.01114985,0.385142,0.009729004,0.190029],"study_design_scores_gemma":[0.00005544215,0.0006350804,0.3655975,0.0007376887,0.0002264588,0.001605041,0.009028476,0.09025978,0.001962112,0.5051895,0.0244347,0.0002682846],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7520632,0.01297748,0.1421045,0.07407417,0.001403741,0.0001366267,0.0006010895,0.0001414238,0.01649771],"genre_scores_gemma":[0.9856618,0.00181468,0.008907476,0.002370756,0.0005007107,0.00006210304,0.00008901433,0.00002877074,0.0005646737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0145792,"threshold_uncertainty_score":0.07710314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710922846099679,"score_gpt":0.2209782866445915,"score_spread":0.2038690581835947,"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."}}