{"id":"W2060797490","doi":"10.1111/j.1365-2419.2007.00449.x","title":"Optimized biophysical model for Icelandic cod (<i>Gadus morhua</i>) larvae","year":2007,"lang":"en","type":"article","venue":"Fisheries Oceanography","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Gadus; Pelagic zone; Range (aeronautics); Abundance (ecology); Icelandic; Oceanography; Fishery; Environmental science; Submarine pipeline; Biology; Geology; Fish <Actinopterygii>","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":[0.0003077275,0.000478914,0.0004740886,0.0003521526,0.0003621254,0.0007435753,0.0007303297,0.0006638305,0.001434401],"category_scores_gemma":[0.0006895038,0.0003956455,0.0005566792,0.0003053291,0.0004172541,0.000334211,0.0003976738,0.0004411369,0.0001739006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001691154,"about_ca_system_score_gemma":0.001837212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1020906,"about_ca_topic_score_gemma":0.04873813,"domain_scores_codex":[0.9998937,0.00003132389,0.000006239068,0.0000263926,0.00001698374,0.00002548703],"domain_scores_gemma":[0.999769,0.00008278642,0.00003764553,0.00001649309,0.00006912198,0.00002490176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006033492,0.000005018559,0.0006273924,0.000002062233,0.000004951707,0.000008159571,0.000002891609,0.9986726,0.0001161521,0.0002265697,0.00005338982,0.0002747621],"study_design_scores_gemma":[0.000007920411,0.000004820015,0.0004854166,0.00000130314,0.000004352275,0.000001724004,0.000004324661,0.9991627,0.00008013221,0.0001504011,0.00009440647,0.000002452375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8556432,0.000193503,0.124842,0.0005079092,0.00005067622,0.0001150759,0.002356735,0.0005731499,0.0157178],"genre_scores_gemma":[0.9869903,0.00005981261,0.009650911,0.00005997889,0.00000907878,0.0001106192,0.0004775488,0.00005121511,0.002590519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1020906,"threshold_uncertainty_score":0.2029927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01774321260060666,"score_gpt":0.245018693535668,"score_spread":0.2272754809350614,"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."}}