{"id":"W2151221031","doi":"10.1002/cjas.1251","title":"Beyond clusters: How regional geographic signature affects firm value and risk","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversification (marketing strategy); Endogeneity; Economic geography; Diversity (politics); Systematic risk; Value (mathematics); Location; Economies of agglomeration; Geographical distance; Business; Sample (material); Economics; Geography; Econometrics; Marketing; Finance; Economic growth; Political science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001431915,0.0001738582,0.0004713004,0.001218882,0.000528176,0.00222228,0.0004688252,0.0004655475,0.003202188],"category_scores_gemma":[0.01266546,0.0001106865,0.0003390062,0.002365972,0.001533819,0.001328552,0.001740549,0.0005580744,0.0002408515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008149034,"about_ca_system_score_gemma":0.0005615893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01188912,"about_ca_topic_score_gemma":0.01272209,"domain_scores_codex":[0.9984757,0.000739754,0.00007316939,0.0002673114,0.0002470489,0.0001968743],"domain_scores_gemma":[0.9781401,0.007809311,0.009469452,0.001309306,0.001118685,0.002153119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001360361,0.00004574256,0.983286,0.00002574642,0.0002099233,0.0001378913,0.0007383602,0.003671857,0.0003251049,0.002306145,0.0004038975,0.008713337],"study_design_scores_gemma":[0.00001148727,0.00008696516,0.9900689,0.00002157864,0.000093222,0.00007971799,0.001542832,0.003245301,0.00022083,0.00391718,0.0006922754,0.00001978765],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967161,0.0002628788,0.0005293506,0.0002785558,0.000004305921,0.000008492446,0.0001209834,0.000006615008,0.002072738],"genre_scores_gemma":[0.9997949,0.00002868935,0.00005079558,0.000009058483,0.000004135336,0.000001019164,0.00002371172,9.361805e-7,0.00008680049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01188912,"threshold_uncertainty_score":0.02363986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04156683257593168,"score_gpt":0.2459757486334118,"score_spread":0.2044089160574801,"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."}}