{"id":"W4406143960","doi":"10.2139/ssrn.5055695","title":"Data Scientists on Wall Street","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Stock (firearms); Portfolio allocation; Portfolio; Competition (biology); Business; Stock market; Private information retrieval; Financial market; Finance; Economics; Monetary economics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002726829,0.002015862,0.003151809,0.008854031,0.001350222,0.007945579,0.001302932,0.001934402,0.7100229],"category_scores_gemma":[0.02408448,0.001498937,0.001239273,0.01465991,0.0008909791,0.005153347,0.004623133,0.003381131,0.7544289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007046994,"about_ca_system_score_gemma":0.002589864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001660519,"about_ca_topic_score_gemma":0.001667901,"domain_scores_codex":[0.9971739,0.0004965644,0.0002896302,0.0008182401,0.00093296,0.0002887838],"domain_scores_gemma":[0.9888257,0.002548112,0.0007815748,0.004913643,0.001463824,0.00146723],"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":[0.0001022999,0.00002528082,0.0002684535,0.0001688339,0.00001482532,0.00002926594,0.00003864217,0.0001022351,0.0002281001,0.003526503,0.9569269,0.03856863],"study_design_scores_gemma":[0.00006101983,0.00001229885,0.0007027517,0.0001629952,0.00001022003,0.00002974133,0.00003572054,0.0003609845,0.0003839187,0.005580734,0.9926445,0.00001506056],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.002678695,0.001447819,0.008873676,0.004983267,0.003862183,0.0003306978,0.5500457,0.04406852,0.3837094],"genre_scores_gemma":[0.01143322,0.002033193,0.008831166,0.0017658,0.001130199,0.0008518643,0.4827073,0.01772461,0.4735227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7100229,"threshold_uncertainty_score":0.4136171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04851499485507733,"score_gpt":0.2634732450154382,"score_spread":0.2149582501603609,"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."}}