{"id":"W1842374574","doi":"10.1139/cjfas-2013-0185","title":"Investigating interconnected fisheries: a coupled model of the lobster and herring fisheries in New England","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Materials Research; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Herring; Fishery; Clupea; Atlantic herring; Homarus; Fisheries management; American lobster; Fishing; Stock assessment; Productivity; Stock (firearms); Fish stock; Geography; Fish <Actinopterygii>; Biology; Economics; Crustacean","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003008839,0.0005121424,0.0005750881,0.0003335149,0.0006512791,0.001517461,0.001458426,0.001332807,0.003761495],"category_scores_gemma":[0.001346469,0.0005233021,0.0007329073,0.0003754819,0.0009857983,0.001274584,0.001464813,0.0007841663,0.0002493942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002563966,"about_ca_system_score_gemma":0.001309225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2531911,"about_ca_topic_score_gemma":0.1678606,"domain_scores_codex":[0.9998637,0.00004448757,0.0000079758,0.00004027454,0.00001298047,0.00003048115],"domain_scores_gemma":[0.9995536,0.000185638,0.00008952371,0.00001975055,0.00006214269,0.00008929877],"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":[0.00008265801,0.00005570292,0.007864201,0.00002944001,0.00006931739,0.0004241019,0.0002146119,0.9778612,0.0007397438,0.01087637,0.000464964,0.001317609],"study_design_scores_gemma":[0.00005523056,0.0000295463,0.002749198,0.000007798409,0.00003441144,0.00003286331,0.0001603277,0.992892,0.00004086479,0.003582188,0.0004001764,0.00001538433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580973,0.0004148909,0.021775,0.001022737,0.00003636246,0.00004417516,0.000499598,0.00006551112,0.01804444],"genre_scores_gemma":[0.9915358,0.0001631985,0.001706588,0.00005632873,0.00001141199,0.00004795228,0.0001269079,0.00001523809,0.006336512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2531911,"threshold_uncertainty_score":0.5034348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0307868479076173,"score_gpt":0.2155703959968852,"score_spread":0.1847835480892679,"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."}}