{"id":"W1984191060","doi":"10.1007/s00168-003-0126-0","title":"Sectors associations and similarities in input-output systems: An application of dual scaling and fuzzy logic to Canada and the United States","year":2003,"lang":"en","type":"article","venue":"The Annals of Regional Science","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Dual (grammatical number); Fuzzy logic; Scaling; Computer science; Mathematics; Artificial intelligence; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002740603,0.000303565,0.0006933233,0.002475065,0.003044485,0.003396015,0.0008629284,0.0006248743,0.002803781],"category_scores_gemma":[0.01614672,0.0002914901,0.0008742069,0.005025134,0.004700076,0.002295349,0.002064757,0.0009690708,0.00006942816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01699628,"about_ca_system_score_gemma":0.01033171,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7192297,"about_ca_topic_score_gemma":0.7320548,"domain_scores_codex":[0.9986321,0.0005329962,0.00006998547,0.0002540978,0.0003295126,0.0001812676],"domain_scores_gemma":[0.992702,0.004678614,0.00059961,0.0003317471,0.001327831,0.0003601555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002747015,0.00006735235,0.03922451,0.00008642516,0.0001305327,0.0004241969,0.00464445,0.08041848,0.0004329669,0.8203127,0.001269027,0.05271456],"study_design_scores_gemma":[0.00007284134,0.00004612858,0.02860419,0.00007245302,0.0001265917,0.0001513159,0.006131101,0.2679691,0.0004258049,0.6901383,0.006184518,0.00007764465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8876348,0.0008992681,0.06963096,0.00214147,0.0000485586,0.0001197057,0.0003295957,0.00008218929,0.03911344],"genre_scores_gemma":[0.9892027,0.0001482969,0.009611629,0.00002726376,0.00000891028,0.00001571994,0.00003123243,0.000005462616,0.0009487531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2807703,"threshold_uncertainty_score":0.5648476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06347386930714555,"score_gpt":0.2743390788003343,"score_spread":0.2108652094931888,"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."}}