{"id":"W3008899997","doi":"10.1016/j.ecolind.2020.106146","title":"Linking individual physiological indicators to the productivity of fish populations: A case study of Atlantic herring","year":2020,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Horizon 2020; National Oceanic and Atmospheric Administration; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Herring; Productivity; Juvenile; Biology; Population; Atlantic herring; Fishing; Fishery; Larva; Ecology; Environmental science; Fish <Actinopterygii>; Demography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006036273,0.0001464024,0.0003130707,0.00008508099,0.0002247205,0.00002076292,0.0006171483,0.000104881,0.002251586],"category_scores_gemma":[0.0006608145,0.00009099846,0.00007080066,0.001532653,0.0003048461,0.00009071027,0.001397347,0.0004001054,0.00002687386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004269966,"about_ca_system_score_gemma":0.00001641025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005341972,"about_ca_topic_score_gemma":0.000504554,"domain_scores_codex":[0.9979445,0.0003237077,0.0004262611,0.0004584278,0.0005376969,0.0003094218],"domain_scores_gemma":[0.9991519,0.0001388028,0.00020851,0.000290669,0.000008672388,0.0002014042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002464622,0.0007631083,0.9889578,0.0000118718,0.00002231997,0.0001207866,0.003124899,0.0003255738,0.0000967368,0.00002422964,0.0005385522,0.005989496],"study_design_scores_gemma":[0.0002201037,0.001380613,0.9935442,0.000002465791,0.00002293366,0.0000184478,0.00274096,0.0000906188,0.0001041993,0.00004169587,0.001709457,0.0001243106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970078,0.000001466743,0.00001392084,0.0009055292,0.00003943936,0.0009222949,0.000007810781,0.00003102222,0.001070676],"genre_scores_gemma":[0.9992591,0.000001514733,0.0001567705,0.000416999,0.00006555322,0.00007405615,0.000005858568,0.000008185107,0.00001201108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005865185,"threshold_uncertainty_score":0.9986605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08538439719327112,"score_gpt":0.3084921229582832,"score_spread":0.2231077257650121,"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."}}