{"id":"W4366769046","doi":"10.1504/ijbem.2023.130476","title":"A bibliometric analysis of sport utility vehicle segment in the automobile industry: two decades study based on web of science database","year":2023,"lang":"en","type":"article","venue":"International Journal of Business and Emerging Markets","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bibliographic coupling; Web of science; Bibliometrics; Field (mathematics); Scientometrics; Data science; Regional science; Database; Computer science; Political science; Citation; Sociology; World Wide Web; MEDLINE","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":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.002284674,0.00007398544,0.0001896558,0.02515638,0.00003780561,0.00003118885,0.0003764821,0.0000227951,0.00005534924],"category_scores_gemma":[0.00009199654,0.00005209543,0.00004314535,0.05665273,0.00007155383,0.0002234774,0.00005396585,0.0001774292,2.215546e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002998792,"about_ca_system_score_gemma":0.00009253861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007040327,"about_ca_topic_score_gemma":0.00001406655,"domain_scores_codex":[0.9986228,0.00001723192,0.0004067982,0.0000919628,0.0007503886,0.0001108165],"domain_scores_gemma":[0.9992294,0.00009079974,0.000149022,0.0001355413,0.0003567092,0.0000385001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007943464,0.0001988812,0.8204821,0.00002567426,0.0001115169,0.00003466146,0.0001939012,0.1607848,0.001486595,0.000004905414,0.0001065588,0.01649099],"study_design_scores_gemma":[0.0003155438,0.00001658166,0.6081789,0.00007563383,0.00003253212,0.000002094863,0.0001978164,0.3908133,0.0002130648,0.000001481576,0.0001228611,0.00003017748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992725,0.00006469445,0.0000668069,0.0001233821,0.0002116444,0.00005432407,0.00001859992,0.000007354996,0.0001807478],"genre_scores_gemma":[0.9997498,0.000146056,0.00004858246,0.00001299298,0.00002855185,0.000002371202,0.000003880572,0.000004365134,0.000003359214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2300285,"threshold_uncertainty_score":0.9858927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02429116140229719,"score_gpt":0.3156399798099579,"score_spread":0.2913488184076607,"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."}}