{"id":"W170979220","doi":"10.2139/ssrn.1474353","title":"Institutional Similarity and Economic Integration","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Similarity (geometry); Political science; Economic geography; Economics; Computer science; Artificial intelligence","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":[0.001968664,0.0001593152,0.0005924304,0.002707775,0.001353032,0.003741933,0.0004405441,0.0006998635,0.009118254],"category_scores_gemma":[0.01030431,0.0001467693,0.0002792362,0.003087746,0.002795008,0.002812995,0.004372017,0.0007326067,0.000522813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008844837,"about_ca_system_score_gemma":0.0006401382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290332,"about_ca_topic_score_gemma":0.001530324,"domain_scores_codex":[0.9986559,0.0005186398,0.00009306399,0.000187268,0.0002550894,0.0002898886],"domain_scores_gemma":[0.9928254,0.002312132,0.002130666,0.000685367,0.0006626903,0.001383892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004742446,0.0007529442,0.5015152,0.00006340138,0.0003072098,0.0003876859,0.005139322,0.004043241,0.0007362875,0.4148284,0.001313775,0.07043828],"study_design_scores_gemma":[0.0001014929,0.0002072289,0.5186236,0.00006100653,0.0001478406,0.0004431056,0.01119738,0.00718368,0.000379717,0.456882,0.004741283,0.00003164669],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609163,0.0003148794,0.001733939,0.0006473907,0.0000125916,0.00001685999,0.00004626986,0.00001235873,0.03629939],"genre_scores_gemma":[0.9993114,0.00003940777,0.0001149645,0.00001559256,0.00001004277,0.000002614526,0.00002028027,0.000001360928,0.0004844307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009118254,"threshold_uncertainty_score":0.03050363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376456764629121,"score_gpt":0.2770101742127549,"score_spread":0.2632456065664637,"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."}}