{"id":"W2901803330","doi":"10.1111/1911-3846.12641","title":"The Effect of Humanizing <scp>Robo‐Advisors</scp> on Investor Judgments*","year":2020,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"AI in Service Interactions","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Task (project management); Investment (military); Key (lock); Computer science; Finance; Marketing; Psychology; Business; Economics; Management; Political science; Computer security; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003056426,0.0004683551,0.0004152146,0.0003682387,0.0006097168,0.001911583,0.0005072308,0.001501378,0.006897727],"category_scores_gemma":[0.04635971,0.0002564198,0.0003362124,0.0002113027,0.000628882,0.001239742,0.0008700768,0.001246251,0.0006733583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005676432,"about_ca_system_score_gemma":0.0004322059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003554401,"about_ca_topic_score_gemma":0.00415206,"domain_scores_codex":[0.9967237,0.001670463,0.0003231275,0.0004332349,0.0005577373,0.000291706],"domain_scores_gemma":[0.8984209,0.06722432,0.02249012,0.005303843,0.001962115,0.004598673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01882531,0.007372748,0.7247787,0.0007110119,0.0006163485,0.0009403733,0.008790234,0.006459234,0.08898802,0.002065107,0.004721289,0.1357317],"study_design_scores_gemma":[0.0003197256,0.004738576,0.9697379,0.00009543219,0.0001609008,0.0002638261,0.003851336,0.007695115,0.007889448,0.001340658,0.003724691,0.0001823736],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962501,0.00003796369,0.0002640828,0.0001106052,0.00001700006,0.00002563312,0.00004992647,0.00002937524,0.00321535],"genre_scores_gemma":[0.9977481,0.00004331315,0.0007996074,0.000159305,0.0000207621,0.00004552783,0.00008238405,0.00001364372,0.001087307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006897727,"threshold_uncertainty_score":0.02307516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09867181203208188,"score_gpt":0.3550335619668928,"score_spread":0.2563617499348109,"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."}}