{"id":"W4307243825","doi":"10.1111/fire.12324","title":"Who uses robo‐advising and how?","year":2022,"lang":"en","type":"article","venue":"Financial Review","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Volatility (finance); Business; Investment (military); Plan (archaeology); Finance; Geography; Political 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":[0.001058723,0.00008837292,0.0002568832,0.0008990772,0.0003403777,0.001702166,0.0005187386,0.0003952448,0.005960919],"category_scores_gemma":[0.008043286,0.00008822708,0.0001964676,0.001359759,0.0002890531,0.001218438,0.0002516449,0.0005257592,0.001088046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004531827,"about_ca_system_score_gemma":0.0008569958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02451667,"about_ca_topic_score_gemma":0.03632397,"domain_scores_codex":[0.9992765,0.0002592439,0.0000581868,0.00006577959,0.000173404,0.0001669411],"domain_scores_gemma":[0.9948255,0.001576968,0.00217048,0.00009774471,0.0004710666,0.0008582684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001365654,0.0002191364,0.771449,0.0003456032,0.00008526377,0.0005027493,0.001551578,0.0001456886,0.0001789026,0.001056865,0.01252293,0.2118057],"study_design_scores_gemma":[0.00001516091,0.0001364995,0.9310001,0.0008475545,0.0001589504,0.002493446,0.01325561,0.0009013038,0.0003570627,0.000797393,0.05000173,0.0000351378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9459296,0.01448048,0.0003847328,0.008391151,0.0001209294,0.00003530213,0.001352263,0.00002074257,0.02928478],"genre_scores_gemma":[0.9850637,0.01000362,0.0002357988,0.0007041667,0.0001039901,0.00001195895,0.000388702,0.000008312199,0.003479766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02451667,"threshold_uncertainty_score":0.04874796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04287471461953474,"score_gpt":0.227239272435718,"score_spread":0.1843645578161832,"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."}}