{"id":"W2364585713","doi":"","title":"The Criterions and Indexing Systrms of the Quantitative Choosing of Regional Leading Industry","year":2002,"lang":"en","type":"article","venue":"","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Search engine indexing; Computer science; Data mining; Artificial intelligence; Information retrieval","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":[0.0173184,0.0005354556,0.0008895184,0.01235937,0.003150394,0.00805077,0.001300387,0.001203124,0.004615243],"category_scores_gemma":[0.05719446,0.000362935,0.0006875277,0.01036384,0.00624908,0.006220898,0.002800199,0.001617179,0.0009046411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003388139,"about_ca_system_score_gemma":0.003934592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003585737,"about_ca_topic_score_gemma":0.003114277,"domain_scores_codex":[0.9858248,0.006492017,0.00159874,0.001052223,0.004353287,0.000678926],"domain_scores_gemma":[0.973224,0.01174153,0.00283804,0.002740215,0.008550243,0.000905946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00009378239,0.00003467457,0.005374966,0.0001934911,0.0000230069,0.00004080804,0.0007880919,0.002261727,0.001852381,0.9273242,0.00308243,0.05893042],"study_design_scores_gemma":[0.0000780225,0.0001207586,0.009089885,0.0001971051,0.00007891857,0.0002198721,0.002121598,0.02285831,0.006228035,0.9288087,0.03006846,0.0001301895],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1172489,0.001566078,0.7472352,0.003549365,0.0003387272,0.0005765621,0.001625739,0.0004203079,0.1274391],"genre_scores_gemma":[0.6368107,0.0007562817,0.3536997,0.0002495388,0.0002517391,0.0005968659,0.0007350627,0.0001481019,0.006752127],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0173184,"threshold_uncertainty_score":0.09158951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0970059277164644,"score_gpt":0.2388188356985868,"score_spread":0.1418129079821224,"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."}}