{"id":"W4388020041","doi":"10.1038/s41558-023-01823-0","title":"Climate change is impacting nutritional security from seafood","year":2023,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Overfishing; Food security; Climate change; Limiting; Micronutrient; Fishery; Aquaculture; Fish stock; Fish <Actinopterygii>; Natural resource economics; Distribution (mathematics); Business; Environmental science; Environmental resource management; Ecology; Biology; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000409502,0.0003835243,0.0003046716,0.0000678065,0.0004890083,0.00008018594,0.0003497027,0.0005796372,0.005306324],"category_scores_gemma":[0.00005603503,0.0003175425,0.0002049395,0.000718828,0.0001803247,0.0009913874,0.0007685461,0.0008360578,0.003093715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005436194,"about_ca_system_score_gemma":0.000002818473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003937837,"about_ca_topic_score_gemma":0.000187427,"domain_scores_codex":[0.9971005,0.00008464419,0.0002717233,0.0007305109,0.000651903,0.001160702],"domain_scores_gemma":[0.9990231,0.0001136214,0.000140056,0.0003962237,0.00001173783,0.0003152765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004145144,0.001322871,0.8660589,0.0005480978,0.0001079454,0.0004711286,0.04425618,0.00001598651,0.007786141,0.0006513559,0.05508927,0.02327765],"study_design_scores_gemma":[0.0007227763,0.0001435346,0.9708486,0.0001071361,0.0000513318,0.00001981448,0.003840273,0.0003917461,0.001439622,0.00382775,0.01795179,0.0006556041],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841956,0.0004304182,5.010841e-7,0.006847905,0.00043199,0.0008855912,0.002267181,0.0003542807,0.004586453],"genre_scores_gemma":[0.9922144,0.001528512,0.0001071852,0.004116183,0.0009365986,0.0002400927,0.0007792332,0.00004263704,0.00003514606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1047898,"threshold_uncertainty_score":0.9999276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02655035195020792,"score_gpt":0.279375125597129,"score_spread":0.2528247736469211,"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."}}