{"id":"W4410070926","doi":"10.3390/fishes10050210","title":"Climate Risk in Intermediate Goods Trade: Impacts on China’s Fisheries Production","year":2025,"lang":"en","type":"article","venue":"Fishes","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); China; Natural resource economics; Fishery; Climate change; Business; Economics; Geography; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001771812,0.0001303802,0.0001389244,0.00003402495,0.0001209014,0.00002965956,0.0001175076,0.00004135429,0.0002642419],"category_scores_gemma":[0.0001990876,0.00009743364,0.00004850494,0.0002275411,0.0001164755,0.0001631781,0.0001539447,0.0001678716,0.00006188687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000742102,"about_ca_system_score_gemma":0.000003634111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004425401,"about_ca_topic_score_gemma":0.00238123,"domain_scores_codex":[0.9991685,0.00005011527,0.000157235,0.0002701106,0.0001174953,0.0002365337],"domain_scores_gemma":[0.9997378,0.00002014532,0.00005084931,0.0001620775,0.000001260756,0.00002785028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004816216,0.00008503347,0.9066603,0.00002577268,0.00001218257,0.000003269028,0.001253766,0.00005042553,0.0002484618,0.0000534962,0.06186718,0.02969196],"study_design_scores_gemma":[0.0001473369,0.00006627477,0.9715631,0.00005003159,0.000009663231,5.736333e-7,0.0001579245,0.00002197724,0.001365344,0.0005885997,0.02592904,0.0001001365],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8930142,0.00003186391,0.000001707282,0.005624014,0.0003397627,0.0001621688,0.000008968414,0.00004712367,0.1007702],"genre_scores_gemma":[0.9976549,0.0004581755,0.00004910054,0.0002725044,0.00006468751,0.00002269983,0.000006981228,0.000005719328,0.001465306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1046407,"threshold_uncertainty_score":0.3973228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007769212027596444,"score_gpt":0.2397518952373617,"score_spread":0.2319826832097653,"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."}}