{"id":"W2383243078","doi":"","title":"Analyzing the Export Instability of China's Aquatic Product Based on the Geographic Concentration","year":2009,"lang":"en","type":"article","venue":"Journal of International Trade","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Diversification (marketing strategy); Instability; Index (typography); Product (mathematics); Economic geography; International trade; Economics; International economics; Business; Geography; Mathematics","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":[0.0007766028,0.00009104059,0.0001293713,0.00009435763,0.00008063539,0.0001001474,0.0004073853,0.00001725499,0.00007242741],"category_scores_gemma":[0.0002220017,0.00004903184,0.0001632091,0.000270838,0.0000611321,0.0003878995,0.000009707208,0.0001775735,0.000001668839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002627222,"about_ca_system_score_gemma":0.00003443534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002082913,"about_ca_topic_score_gemma":0.000003270615,"domain_scores_codex":[0.9989284,0.00003123394,0.0004045941,0.00008980146,0.0004530046,0.00009297499],"domain_scores_gemma":[0.9991328,0.00008549347,0.0005565865,0.0001299355,0.00008777533,0.000007456026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000547983,0.001324952,0.754204,0.0000631112,0.0002184761,0.00002791235,0.0001676854,0.007698007,0.005025082,0.219368,0.0009426998,0.01041204],"study_design_scores_gemma":[0.0003534713,0.00004575491,0.9834505,0.0001051208,0.00004235203,0.000005777865,0.00008336386,0.006579081,0.0007104388,0.004347828,0.004212207,0.00006407875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9334177,0.0001209278,0.0005640314,0.05688097,0.0004918602,0.0001544075,0.000001749487,0.000008562259,0.008359808],"genre_scores_gemma":[0.9980153,0.00001151282,0.00003637033,0.001313773,0.0006112838,0.000001314219,0.00000323436,0.00000352449,0.00000371242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2292465,"threshold_uncertainty_score":0.199946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636718961832906,"score_gpt":0.2342228677209179,"score_spread":0.2178556781025889,"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."}}