{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","sts","scholarly_communication"],"consensus_categories":["metaresearch","bibliometrics"],"category_scores_codex":[0.04579156,0.000141747,0.0003852962,0.4579124,0.002710158,0.003224901,0.004321679,0.00005728827,0.0008322586],"category_scores_gemma":[0.06613276,0.00007588873,0.0001904289,0.9332033,0.0009287017,0.000262224,0.004567885,0.0008147171,0.000008488772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009071187,"about_ca_system_score_gemma":0.0001014276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003992726,"about_ca_topic_score_gemma":0.00006567907,"domain_scores_codex":[0.9874342,0.001344046,0.0007662438,0.0008017862,0.008958422,0.0006952708],"domain_scores_gemma":[0.9734995,0.02346299,0.0003916944,0.00123013,0.001319393,0.00009627197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002900872,0.0001209105,0.1359336,0.00003113325,0.0003165044,0.00004344908,0.006877566,0.01238508,0.001422461,0.005326684,0.0264329,0.8108196],"study_design_scores_gemma":[0.0004467471,0.0001915804,0.7536237,0.000005003241,0.00003293658,0.00001377112,0.004284983,0.03741937,0.000305433,0.00864981,0.1948157,0.0002110033],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908596,0.004363499,0.001531282,0.0009825161,0.0004493016,0.0003150382,0.0001168271,0.00001026459,0.001371642],"genre_scores_gemma":[0.9971908,0.00035385,0.00018623,0.00004916212,0.0001091299,0.00002964315,0.000003870935,0.000009378944,0.002067874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8106086,"threshold_uncertainty_score":0.9985882,"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."}}