{"id":"W2054556883","doi":"10.5539/jas.v3n1p212","title":"Empirical Analysis on the Relationship between Tourism Development and Economic Growth in Sichuan","year":2011,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tourism; Variance decomposition of forecast errors; Pillar; Economics; Econometric analysis; Government (linguistics); Economic geography; Econometric model; Variance (accounting); Econometrics; Regional science; Economy; Geography; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001109447,0.0002136159,0.0003241285,0.001618229,0.0005663036,0.0007953388,0.0004281635,0.0002995789,0.001921803],"category_scores_gemma":[0.003045477,0.0001525961,0.0005320772,0.002224045,0.0004747665,0.0003841814,0.0005501035,0.0007453976,0.0001414555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008032,"about_ca_system_score_gemma":0.001980275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07871097,"about_ca_topic_score_gemma":0.06482939,"domain_scores_codex":[0.9995659,0.0001158944,0.00003098986,0.00006424213,0.00008870681,0.0001342885],"domain_scores_gemma":[0.9970613,0.001699033,0.0004205393,0.000084211,0.0003365315,0.0003983687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002556847,0.00005565368,0.993601,0.00001624369,0.00006656333,0.0003939381,0.0003432984,0.001435853,0.00005989423,0.0004929063,0.0004192565,0.003089877],"study_design_scores_gemma":[0.000005035098,0.00003018392,0.9872524,0.00001866655,0.00006294074,0.00008679537,0.001554316,0.01011052,0.00009410172,0.0002293618,0.0005481767,0.000007538199],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983352,0.0001512094,0.0001694753,0.0001486877,0.000004759597,0.000005805811,0.0001675823,0.000006260682,0.001011173],"genre_scores_gemma":[0.999121,0.0001095749,0.00006283858,0.00001361688,0.00000777385,0.000005614186,0.0003664118,0.000001014215,0.0003122269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07871097,"threshold_uncertainty_score":0.1565056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1019896682875926,"score_gpt":0.2471053730821102,"score_spread":0.1451157047945175,"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."}}