{"id":"W2364548782","doi":"","title":"Analysis on differences in urban competitiveness and the influential factors——A Case of Gansu Province","year":2009,"lang":"en","type":"article","venue":"Ganhanqu ziyuan yu huanjing","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Economic geography; Principal component analysis; Index (typography); Regional science; Business; Geography; Computer science; Mathematics; Statistics","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":[0.0005742016,0.0001943265,0.0002025286,0.001363597,0.0007913943,0.0008330283,0.0004544669,0.00021955,0.001762037],"category_scores_gemma":[0.0008935635,0.0001104837,0.0005350122,0.00216443,0.0006666582,0.0003386797,0.0005754667,0.0002787534,0.00007122721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003211927,"about_ca_system_score_gemma":0.001113457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2507634,"about_ca_topic_score_gemma":0.2361486,"domain_scores_codex":[0.9996151,0.0001368975,0.00001217651,0.00004554322,0.00005569922,0.0001346903],"domain_scores_gemma":[0.999504,0.0001745832,0.00008100715,0.0000342624,0.0001282674,0.00007787484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002221468,0.0001475542,0.945962,0.0000703012,0.0001359947,0.006228629,0.003168209,0.01026984,0.0007294168,0.01403316,0.001541835,0.01749096],"study_design_scores_gemma":[0.00001738528,0.0000430031,0.958434,0.00001841204,0.00008240213,0.0003951491,0.01133845,0.02586461,0.000249162,0.001171877,0.002366206,0.00001933295],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970234,0.00004410387,0.0001407979,0.00009170006,0.000001711837,0.000006323413,0.00005285574,0.000002763572,0.002636465],"genre_scores_gemma":[0.999548,0.00003092854,0.00009010299,0.000004820058,0.000001311243,0.000002182178,0.00005118382,5.727179e-7,0.0002708027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2507634,"threshold_uncertainty_score":0.4986076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02237279643310451,"score_gpt":0.2099673405256331,"score_spread":0.1875945440925286,"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."}}