{"id":"W4322581580","doi":"10.3354/meps14269","title":"Rebuilding Mediterranean marine resources under climate change","year":2023,"lang":"en","type":"article","venue":"Marine Ecology Progress Series","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; Agence Nationale de la Recherche; Deutsche Forschungsgemeinschaft; Natural Sciences and Engineering Research Council of Canada; Centre Méditerranéen de l’Environnement et de la Biodiversité; European Commission; Center for Neuroscience and Regenerative Medicine; Biodiversa+","keywords":"Fishing; Climate change; Marine protected area; Marine ecosystem; Mediterranean climate; Marine conservation; Environmental science; Mediterranean sea; Fishery; Ecosystem; Biomass (ecology); Pelagic zone; Biodiversity; Effects of global warming on oceans; Context (archaeology); Fisheries management; Ecology; Global warming; Geography; Environmental resource management; Biology; Habitat","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0006399994,0.0003945106,0.0003244999,0.0003403579,0.0003108522,0.001287975,0.0006468272,0.0006781718,0.00153994],"category_scores_gemma":[0.0014198,0.0001272227,0.0005310048,0.0004096438,0.0004548001,0.001625993,0.001223527,0.0003671687,0.0003043015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001247797,"about_ca_system_score_gemma":0.0009591321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02519229,"about_ca_topic_score_gemma":0.02094914,"domain_scores_codex":[0.9998406,0.00005986529,0.000009115774,0.00002937639,0.00002376048,0.00003730768],"domain_scores_gemma":[0.9997594,0.00003189199,0.00004937376,0.00004770187,0.00005989383,0.00005177746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002400585,0.0001477153,0.412191,0.0005458078,0.0008711676,0.003319265,0.003032461,0.3393291,0.02163612,0.02608407,0.01360793,0.1789954],"study_design_scores_gemma":[0.00007119169,0.0003669116,0.5796767,0.0002259354,0.0002750283,0.0006000726,0.006006936,0.2860483,0.002539196,0.04809048,0.07598416,0.0001151426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775252,0.0009542893,0.005766136,0.00223699,0.0001057142,0.00002433108,0.0005553663,0.0001640826,0.01266792],"genre_scores_gemma":[0.9961107,0.0005104769,0.002448248,0.0001630315,0.00002119398,0.00001339298,0.0001769396,0.00002492747,0.000530992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02519229,"threshold_uncertainty_score":0.05009133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03480770774386462,"score_gpt":0.280908404068727,"score_spread":0.2461006963248623,"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."}}