{"id":"W4402390234","doi":"10.24818/rfb.23.16.01.05","title":"Mapping the Intellectual Structure of Asset Pricing: A Bibliometric Study","year":2024,"lang":"en","type":"article","venue":"The Review of Finance and Banking","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Capital asset pricing model; Business; Asset (computer security); Computer science; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001164119,0.0001151515,0.0005775664,0.00205604,0.0001070619,0.00005486627,0.0002854532,0.00002338461,0.0002768046],"category_scores_gemma":[0.0001708198,0.0000659721,0.0001548216,0.01746636,0.00006312992,0.00008877904,0.0001156227,0.0001377067,0.00001010703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001414231,"about_ca_system_score_gemma":0.00001469185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002173604,"about_ca_topic_score_gemma":0.00001310151,"domain_scores_codex":[0.9988164,0.00003737337,0.0007279936,0.0002185899,0.00006641719,0.0001332221],"domain_scores_gemma":[0.9989569,0.0002814943,0.0003523893,0.0003596772,0.00004027483,0.000009275287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002113794,0.0002273271,0.03389848,0.0385621,0.001961098,0.00001406993,0.02222722,0.0001001059,0.0002252351,0.2557139,0.009058801,0.6379905],"study_design_scores_gemma":[0.0004722511,0.0005812164,0.1166006,0.02262878,0.0003654741,0.00007686417,0.002640315,0.008598667,0.0001145881,0.02409588,0.8230696,0.0007557659],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3443002,0.6533676,0.0005409184,0.0003986581,0.0001071278,0.0003325992,0.0000305944,0.000007533675,0.0009147596],"genre_scores_gemma":[0.8950489,0.1046792,0.00004010902,0.00006677122,0.0000501963,0.000006048765,0.000001615311,0.00000850884,0.00009867995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8140107,"threshold_uncertainty_score":0.8392007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05032413445812774,"score_gpt":0.2596479783219227,"score_spread":0.2093238438637949,"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."}}