{"id":"W4413468549","doi":"10.2139/ssrn.5392628","title":"Serial Acquisitions in Tech ","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Business; Chemistry; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001543942,0.00126305,0.001427943,0.003590478,0.001139007,0.006306022,0.0008583741,0.002242432,0.233461],"category_scores_gemma":[0.008029165,0.0007074995,0.000365408,0.00951727,0.0006805339,0.004632949,0.00121429,0.001865517,0.0770383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003828261,"about_ca_system_score_gemma":0.002146161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02408697,"about_ca_topic_score_gemma":0.03846563,"domain_scores_codex":[0.9989411,0.0001272532,0.0001206236,0.0002900605,0.0003978353,0.0001230702],"domain_scores_gemma":[0.9965941,0.001041872,0.0008129182,0.0003576359,0.0008570281,0.0003363824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001315366,0.00005536187,0.002667348,0.0001902053,0.00002119825,0.0001008098,0.00008271039,0.000451268,0.0001577376,0.02423474,0.9081942,0.06371288],"study_design_scores_gemma":[0.000108719,0.00005239778,0.01590635,0.0002777704,0.00004403197,0.0002104839,0.0001444416,0.002642257,0.001592249,0.02529795,0.9536911,0.0000322462],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0231683,0.01682806,0.007541419,0.04404981,0.008823385,0.0001858147,0.1862467,0.004940468,0.7082161],"genre_scores_gemma":[0.06914028,0.005619402,0.003294984,0.0007307547,0.002341517,0.0001160918,0.04163364,0.001088906,0.8760344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.233461,"threshold_uncertainty_score":0.781005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02383426060809381,"score_gpt":0.2502600388611751,"score_spread":0.2264257782530814,"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."}}