{"id":"W2160655971","doi":"10.5267/j.msl.2013.01.027","title":"Ranking insurance firms using AHP and Factor Analysis","year":2013,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytic hierarchy process; Ranking (information retrieval); Cash flow; Quality (philosophy); Variance (accounting); Actuarial science; Business; Econometrics; Economics; Statistics; Computer science; Mathematics; Finance; Operations research; Accounting","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005231932,0.0001718904,0.0003135044,0.001035847,0.000411555,0.000435697,0.0004720542,0.00002738697,0.0001803239],"category_scores_gemma":[0.00001794667,0.0001863423,0.00009967072,0.002161477,0.0002973577,0.001089662,0.0002342371,0.00008758174,0.0002818219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215183,"about_ca_system_score_gemma":0.000001891958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00064142,"about_ca_topic_score_gemma":0.000008934818,"domain_scores_codex":[0.9982167,0.000007336592,0.0004125408,0.0006899838,0.0001387588,0.0005346914],"domain_scores_gemma":[0.9992462,0.00001141163,0.0002256659,0.0004249192,0.00001375358,0.00007801668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002861347,0.00002878595,0.9507486,0.00003998022,0.0001561639,0.000009096819,0.0004155318,0.001554142,0.0004121065,0.0377634,0.0002501566,0.008619145],"study_design_scores_gemma":[0.0002421803,0.00000917062,0.9821547,0.00001019605,0.00002531187,3.639543e-7,0.00007861719,0.01176898,0.00003153438,0.002274491,0.003122019,0.0002824806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587219,0.0001651247,0.03264461,0.001257645,0.0003027254,0.0003929736,0.00001230505,0.00004073871,0.006461943],"genre_scores_gemma":[0.9936128,0.000112978,0.003298845,0.002678413,0.00004069441,0.00003220987,0.00000171723,0.00001113063,0.0002112352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03548891,"threshold_uncertainty_score":0.7598819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02272494088086396,"score_gpt":0.2147837886367344,"score_spread":0.1920588477558705,"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."}}