{"id":"W4385212305","doi":"10.5465/amproc.2023.17264abstract","title":"The Face of Fortune: A Review on How Machine Learning Can Address Limitations in Past Research","year":2023,"lang":"en","type":"review","venue":"Academy of Management Proceedings","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Generalizability theory; Face (sociological concept); Perception; Standardization; Data science; Computer science; Artificial intelligence; Psychology; Cognitive psychology; Machine learning; Sociology; Social 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01159574,0.0008695169,0.002548702,0.006854709,0.0006960167,0.003163904,0.001875421,0.002066685,0.003641026],"category_scores_gemma":[0.03396088,0.0007886915,0.001539257,0.007182106,0.001911719,0.004266405,0.00136372,0.002600458,0.0009827005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00230196,"about_ca_system_score_gemma":0.005458144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004082083,"about_ca_topic_score_gemma":0.0080224,"domain_scores_codex":[0.9966419,0.001349104,0.0007851562,0.0004133018,0.00071994,0.00009058435],"domain_scores_gemma":[0.9588803,0.03635143,0.001321578,0.0005341104,0.002640011,0.0002725217],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006481911,0.00003646579,0.0005700213,0.07475689,0.0004167935,0.0000762376,0.0002701881,0.0004645005,0.0001342631,0.01004597,0.02141036,0.8917536],"study_design_scores_gemma":[0.00002925489,0.0001214998,0.002428763,0.1541613,0.0009429096,0.0003792949,0.0004312696,0.00033187,0.0002643994,0.01562623,0.8252151,0.00006808261],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000581693,0.9977506,0.0001997259,0.001401324,0.0001633509,0.000007023449,0.00001832121,0.000003513941,0.0003980229],"genre_scores_gemma":[0.001307741,0.9968271,0.0005391895,0.0009117672,0.0002633927,0.00002515508,0.00003018175,0.00000418298,0.00009130419],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9884043,"threshold_uncertainty_score":0.06132489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4821372504185864,"score_gpt":0.4291190428705017,"score_spread":0.05301820754808467,"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."}}