{"id":"W4312081906","doi":"10.1108/mf-07-2022-0330","title":"Mapping the intellectual structure and demystifying the research trend of cross listing: a bibliometric analysis","year":2022,"lang":"en","type":"article","venue":"Managerial Finance","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Listing (finance); Originality; Scopus; Field (mathematics); Bibliographic coupling; Computer science; Publication; Data science; Sociology; Library science; Political science; Social science; Citation; Qualitative research; Business; Law; Mathematics","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01492206,0.0005833594,0.001211074,0.125739,0.001443529,0.008096785,0.0008269756,0.00053474,0.004105445],"category_scores_gemma":[0.04436186,0.0002402048,0.001197182,0.1333423,0.001102318,0.005568478,0.003228087,0.0004631425,0.0006479525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00235326,"about_ca_system_score_gemma":0.005038635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003351578,"about_ca_topic_score_gemma":0.004248004,"domain_scores_codex":[0.9882803,0.00271383,0.002734915,0.001072076,0.004669082,0.0005297998],"domain_scores_gemma":[0.9384066,0.03344084,0.01284895,0.002792752,0.01146115,0.001049724],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002883368,0.0001471612,0.4790953,0.01411356,0.00103287,0.001019991,0.01400332,0.002023384,0.004976384,0.01652853,0.006854108,0.4599171],"study_design_scores_gemma":[0.00004221009,0.0004252341,0.8423382,0.006679795,0.001616766,0.002003061,0.04270441,0.009569514,0.006186646,0.01463906,0.07363224,0.0001628837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8932697,0.02898716,0.02386374,0.002677871,0.0002049732,0.001711506,0.0128374,0.0004482988,0.03599934],"genre_scores_gemma":[0.9533298,0.01015608,0.02538885,0.0001308408,0.0001917828,0.0009086542,0.007899175,0.00006897975,0.001925875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9850779,"threshold_uncertainty_score":0.07891637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.643601084985468,"score_gpt":0.5594661742887042,"score_spread":0.08413491069676382,"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."}}