{"id":"W2382608696","doi":"","title":"Comparison between the roles at the levels of state or provincial government in aquaculture industry","year":2006,"lang":"en","type":"article","venue":"Chinese Fisheries Economics","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nomothetic and idiographic; Government (linguistics); China; Aquaculture; Business; State (computer science); Function (biology); Economic growth; Economics; Fish <Actinopterygii>; Political science; Fishery","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":[0.0004498348,0.0002380139,0.0007271909,0.00004602684,0.0001719446,0.0000892984,0.000490257,0.0001850446,0.0004988699],"category_scores_gemma":[0.0000589543,0.000145734,0.0001978231,0.000165238,0.0002563975,0.0002238094,0.0001952845,0.0003172072,0.00005513364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003911374,"about_ca_system_score_gemma":0.00004449837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002177927,"about_ca_topic_score_gemma":0.03826085,"domain_scores_codex":[0.9981419,0.00002656245,0.001180967,0.0003495554,0.00003991523,0.0002611153],"domain_scores_gemma":[0.9985542,0.0001779359,0.0008149095,0.0003971187,0.00001477916,0.0000410686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006499869,0.00004699485,0.9871711,0.00001193429,0.00008282396,6.888254e-7,0.0006054807,0.005173496,0.000002460847,0.004184775,0.001668185,0.0009871159],"study_design_scores_gemma":[0.0004969767,0.00004342097,0.9331323,0.000006267729,0.00001320854,0.000001683061,0.0003372938,0.00343814,0.00008126894,0.01904047,0.04314797,0.000261033],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858233,0.0002978565,0.00008008892,0.003751132,0.000124761,0.0002446516,0.001268069,0.000009498585,0.008400623],"genre_scores_gemma":[0.9936514,0.00006733281,0.00004058748,0.0001850599,0.0002547278,0.00003114238,0.00004160236,0.00002294226,0.005705228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05403877,"threshold_uncertainty_score":0.9792884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03268334129380113,"score_gpt":0.2297650470859229,"score_spread":0.1970817057921218,"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."}}