{"id":"W2807256018","doi":"","title":"FUSÕES E AQUISIÇÕES SOB A LENTE DA GOVERNANÇA CORPORATIVA: ANÁLISE SOCIOMÉTRICA E BIBLIOMÉTRICA DOS AUTORES DE REFERÊNCIA INTERNACIONAL","year":2017,"lang":"pt","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Business and Management Studies","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Scopus; Bibliometrics; Library science; Population; Corporate governance; Web of science; Sociology; Political science; Management; Computer science; MEDLINE; Economics","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01827319,0.0003937965,0.000864525,0.03383701,0.00164217,0.006113259,0.0008235254,0.000525266,0.002668383],"category_scores_gemma":[0.07189701,0.0003199964,0.0005951066,0.06142497,0.002041839,0.003312675,0.002830829,0.0004944896,0.0003827594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00268244,"about_ca_system_score_gemma":0.003319189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01217946,"about_ca_topic_score_gemma":0.01459168,"domain_scores_codex":[0.978714,0.0054,0.003163646,0.001955406,0.01010749,0.0006593217],"domain_scores_gemma":[0.9157359,0.0423072,0.02217909,0.004202039,0.01449645,0.001079264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008941693,0.00004282422,0.8544814,0.001836413,0.0003469639,0.0003378036,0.02761026,0.0004779958,0.0006412657,0.006743692,0.002573047,0.104819],"study_design_scores_gemma":[0.00001093274,0.00009103255,0.8871373,0.001137479,0.0002739042,0.0006797406,0.03605477,0.001359372,0.001076104,0.00301227,0.06911547,0.00005161899],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9306077,0.01153487,0.003030118,0.001101819,0.0001053907,0.0001949063,0.005846977,0.0001745107,0.04740363],"genre_scores_gemma":[0.9886153,0.004496901,0.003132718,0.00005020857,0.0001544676,0.0001620904,0.001990554,0.0000321863,0.00136554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.966163,"threshold_uncertainty_score":0.09663904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07447990752880776,"score_gpt":0.321786251249057,"score_spread":0.2473063437202493,"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."}}