{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004845419,0.0005678696,0.0002358557,0.0006107719,0.0004169565,0.001240442,0.0004300856,0.0004766615,0.001943605],"category_scores_gemma":[0.0006333747,0.0001935469,0.0009981195,0.0007523696,0.0004890306,0.0007463067,0.0009391297,0.0003951497,0.00009886128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002346349,"about_ca_system_score_gemma":0.00233599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06237746,"about_ca_topic_score_gemma":0.05490565,"domain_scores_codex":[0.9997906,0.00004480316,0.00001290063,0.00004300463,0.00003966385,0.00006908498],"domain_scores_gemma":[0.999754,0.00006482298,0.00006274188,0.00001970676,0.0000461856,0.00005249855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002009824,0.0001396853,0.5702555,0.0001226056,0.000359044,0.00122978,0.0003725098,0.3963802,0.00273671,0.01038827,0.001188768,0.01662598],"study_design_scores_gemma":[0.00004103089,0.0002288709,0.5114995,0.0000659528,0.0003232487,0.0001639111,0.0007363656,0.4741856,0.001999602,0.007274172,0.003411295,0.00007042036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929157,0.0002338787,0.00192218,0.0004042674,0.00001147922,0.00001917844,0.0003873028,0.0000280813,0.00407773],"genre_scores_gemma":[0.9988287,0.0001525258,0.000175396,0.00001822617,0.000002735617,0.000005616698,0.0001623501,0.000001961351,0.0006524208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06237746,"threshold_uncertainty_score":0.1240287,"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."}}