{"id":"W4410589767","doi":"10.1038/s44183-025-00124-7","title":"How to leverage trade to achieve a 2050 ocean dream","year":2025,"lang":"en","type":"letter","venue":"npj Ocean Sustainability","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Leverage (statistics); Dream; Business; Environmental science; Oceanography; Computer science; Geology; Artificial intelligence; Psychology; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005594255,0.0005051288,0.0005302381,0.0004633784,0.005704452,0.007135782,0.001477666,0.04673981,0.009226986],"category_scores_gemma":[0.01693183,0.000451552,0.0008220095,0.0004272721,0.006508569,0.01111164,0.004521054,0.04504293,0.006000952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004350793,"about_ca_system_score_gemma":0.01096959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007393027,"about_ca_topic_score_gemma":0.01429875,"domain_scores_codex":[0.997288,0.0006643486,0.0001775027,0.0002755512,0.001023756,0.0005709045],"domain_scores_gemma":[0.9942535,0.002416335,0.0002637376,0.000282095,0.0009542087,0.001830143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001812991,0.00004431988,0.0004217741,0.00003669593,0.000007116246,0.000520013,0.000305513,0.0001200795,0.000232164,0.03650369,0.9485535,0.01323698],"study_design_scores_gemma":[0.00002324167,0.00003146182,0.0003901043,0.0001261536,0.000003998868,0.0004520932,0.0011709,0.0003703904,0.0001648643,0.04620398,0.9510265,0.00003642722],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0002460144,0.0006609886,0.0001875442,0.9888806,0.005025771,0.00000592956,0.00001749915,0.00001725958,0.004958465],"genre_scores_gemma":[0.003882786,0.0005343433,0.0004242148,0.9842933,0.004142958,0.00001926696,0.00001761566,0.00001495985,0.006670695],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04673981,"threshold_uncertainty_score":0.03156739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005859006200789453,"score_gpt":0.2149261062611242,"score_spread":0.2090671000603348,"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."}}