{"id":"W2193034424","doi":"10.1002/met.1539","title":"Assessment of the benefits of the Chinese Public Weather Service","year":2015,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Key Research and Development Program of China; Nanjing University; China Meteorological Administration; National Natural Science Foundation of China","keywords":"China; Receipt; Service (business); Business; Gross domestic product; Product (mathematics); Public opinion; Agricultural economics; Geography; Marketing; Economic growth; Economics; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002158743,0.0002911401,0.0002547204,0.001281,0.0005394074,0.001069321,0.00035376,0.00041887,0.004608457],"category_scores_gemma":[0.005668518,0.0001039715,0.0006057751,0.001111343,0.0006001219,0.0008252827,0.0008366654,0.0004405445,0.0001937168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003725675,"about_ca_system_score_gemma":0.002343352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02746197,"about_ca_topic_score_gemma":0.02681644,"domain_scores_codex":[0.9984957,0.0005063866,0.00007385581,0.00007061525,0.000639291,0.0002141894],"domain_scores_gemma":[0.9964889,0.00113877,0.0008080817,0.0001500055,0.001058225,0.0003559942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007168534,0.0005500352,0.8459292,0.0005716541,0.000337328,0.0008491917,0.002818257,0.01024496,0.003134398,0.006914136,0.004576727,0.1233572],"study_design_scores_gemma":[0.00003676261,0.0005304621,0.9634144,0.00009212067,0.0002560783,0.0001265792,0.007100215,0.02063717,0.0007799136,0.001177259,0.005797356,0.00005161109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871138,0.0003525082,0.0004312094,0.0007068466,0.00002069809,0.00006195973,0.000217387,0.000011036,0.01108444],"genre_scores_gemma":[0.9991584,0.00009435054,0.0001240071,0.00002731077,0.00001053155,0.00001093095,0.0000685593,0.000001044056,0.0005048797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02746197,"threshold_uncertainty_score":0.05460423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1257469350416522,"score_gpt":0.2538451467950771,"score_spread":0.1280982117534249,"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."}}