{"id":"W6920773115","doi":"10.6084/m9.figshare.20288523.v1","title":"Optimal dynamic spatial closures can improve fishery yield and reduce fishing-induced habitat damage","year":2022,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Yield (engineering); Habitat; Fishing; Aquatic ecosystem; Fish <Actinopterygii>","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006325609,0.0007591686,0.0004036273,0.0007346691,0.0005339317,0.0009326222,0.001602903,0.0007961755,0.08435524],"category_scores_gemma":[0.006171638,0.0003420366,0.0005643452,0.0004979612,0.0004453804,0.001002593,0.001481371,0.0006715091,0.01268206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009001396,"about_ca_system_score_gemma":0.001227607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0101823,"about_ca_topic_score_gemma":0.01609544,"domain_scores_codex":[0.9996781,0.0000404696,0.00002954586,0.00008059709,0.000111555,0.00005971166],"domain_scores_gemma":[0.9985097,0.0006643611,0.000132118,0.0002200095,0.0003528994,0.0001208731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001634452,0.0005387097,0.01041298,0.0005205681,0.00006609495,0.0003905868,0.0002267695,0.2459897,0.01609187,0.0311533,0.25377,0.439205],"study_design_scores_gemma":[0.0003502587,0.0001453072,0.003565369,0.0001078867,0.00004282577,0.0001610523,0.00005464998,0.9030838,0.01601106,0.01671053,0.05968925,0.00007807819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0821739,0.0005702361,0.6697003,0.00150143,0.0008031173,0.0004236888,0.022484,0.1421352,0.0802082],"genre_scores_gemma":[0.5630122,0.0004212222,0.3524157,0.0003010434,0.0001261133,0.0007760077,0.01877296,0.01689556,0.04727921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08435524,"threshold_uncertainty_score":0.2821964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03012955851639676,"score_gpt":0.2668649005838887,"score_spread":0.236735342067492,"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."}}