{"id":"W4409787754","doi":"10.61091/jcmcc127a-516","title":"Machine learning in corporate M and A valuation: an empirical study based on big data","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Impact of AI and Big Data on Business and Society","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Valuation (finance); Big data; Empirical research; Business; Computer science; Data science; Accounting; Data mining; Statistics; Mathematics","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":[0.005051472,0.0003319163,0.0004037936,0.002887417,0.000830969,0.001563431,0.0006994522,0.0009394264,0.001235084],"category_scores_gemma":[0.02228897,0.0002119458,0.000618622,0.003592802,0.0009766504,0.004101207,0.001019928,0.001604289,0.0002750655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00116252,"about_ca_system_score_gemma":0.0007482344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004873738,"about_ca_topic_score_gemma":0.004726104,"domain_scores_codex":[0.9976971,0.001044591,0.0001521582,0.0002279349,0.0006092337,0.0002690557],"domain_scores_gemma":[0.9571654,0.03336802,0.00446586,0.001431764,0.002150444,0.001418448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009353089,0.0007804584,0.9524375,0.00007318179,0.00009215295,0.0004383638,0.0009922013,0.008064089,0.0001187627,0.006517529,0.001691572,0.02870059],"study_design_scores_gemma":[0.00002596544,0.0002980969,0.7972015,0.0002056228,0.00009628086,0.0004762897,0.005457258,0.1826705,0.0005540253,0.009391661,0.003572146,0.00005072241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949279,0.0005125253,0.001540704,0.0007840818,0.00001247238,0.0000252229,0.0001683906,0.000008585573,0.00202015],"genre_scores_gemma":[0.9988758,0.0002343454,0.00044186,0.00005448524,0.00002083705,0.00001348913,0.000168702,0.000002242698,0.0001881679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005051472,"threshold_uncertainty_score":0.0267151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2243132743679613,"score_gpt":0.4091957171829276,"score_spread":0.1848824428149664,"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."}}