{"id":"W4394862587","doi":"10.2139/ssrn.4787505","title":"Geographical Proximity, Cultural Familiarity and Financial Information Production","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Economic Growth and Development","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Production (economics); Business; Finance; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009687198,0.00008758112,0.00007636601,0.0001379777,0.0001788397,0.0004104123,0.00019446,0.00005260669,0.000001027625],"category_scores_gemma":[0.00005303074,0.00007007215,0.00004182151,0.0002351872,0.00003010211,0.002708209,0.00007827651,0.0008764306,0.00002350349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002611344,"about_ca_system_score_gemma":0.001220609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001635595,"about_ca_topic_score_gemma":0.00008551828,"domain_scores_codex":[0.9987308,0.00002364461,0.0002055408,0.0001572339,0.000127538,0.000755276],"domain_scores_gemma":[0.9997518,0.000009076192,0.00003965007,0.00008315601,0.00005317271,0.00006312528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006733067,0.00001157397,0.002784269,0.00001706882,0.00002114582,0.000001330724,0.0006162556,0.000004187017,0.00002179577,0.8169752,0.0004127607,0.1791276],"study_design_scores_gemma":[0.0002842766,0.0001953537,0.02027146,0.0000362989,0.00001050088,0.002001118,0.0002303552,0.008339019,0.0001676402,0.9521002,0.01609302,0.0002708178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8174966,0.001849645,0.1736035,0.004954875,0.001261656,0.0001577616,4.968302e-7,0.0001435515,0.0005319169],"genre_scores_gemma":[0.9966757,0.001659294,0.001222257,0.0001233478,0.0001941276,0.000005823206,0.000001873736,0.000002422228,0.0001151145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1791791,"threshold_uncertainty_score":0.3957615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004934883197127574,"score_gpt":0.201016532137241,"score_spread":0.1960816489401134,"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."}}