{"id":"W2139085708","doi":"10.1007/s11192-011-0603-7","title":"ASEAN benchmarking in terms of science, technology, and innovation from 1999 to 2009","year":2012,"lang":"en","type":"article","venue":"Scientometrics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"","keywords":"Benchmarking; Regional science; Scientometrics; Political science; Business; Data science; Knowledge management; Computer science; Library science; Sociology; Marketing","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003425148,0.0002900931,0.0002328067,0.003060024,0.0004133636,0.001234803,0.0003985501,0.0002470543,0.001025733],"category_scores_gemma":[0.007934461,0.00007534133,0.0002312543,0.01017467,0.0003746804,0.001183692,0.0008923647,0.0004058727,0.0004291461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001924316,"about_ca_system_score_gemma":0.001441656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03693071,"about_ca_topic_score_gemma":0.05096745,"domain_scores_codex":[0.9982923,0.0003988628,0.000160235,0.0001393595,0.0008208551,0.000188427],"domain_scores_gemma":[0.9933786,0.001073221,0.002044385,0.0003945382,0.002895928,0.0002131911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000388904,0.0002180015,0.7172561,0.0003501223,0.0001798045,0.0004522397,0.001327766,0.02015351,0.001270645,0.01255305,0.03816668,0.2076832],"study_design_scores_gemma":[0.00000541809,0.0001103723,0.9462987,0.0000804183,0.00004797735,0.0002959413,0.0009402753,0.00656066,0.001829228,0.0008707652,0.04293085,0.00002934209],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9185343,0.002987361,0.002592353,0.0009844241,0.00006454811,0.00002583588,0.01694601,0.0002275307,0.05763767],"genre_scores_gemma":[0.9825515,0.001127539,0.001081924,0.00006825629,0.00002727068,0.00002210638,0.01171636,0.00001580426,0.00338923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.99694,"threshold_uncertainty_score":0.07343149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06945695606174171,"score_gpt":0.2658784472932594,"score_spread":0.1964214912315177,"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."}}