{"id":"W4410058326","doi":"10.1111/ijsa.70012","title":"A Registered Report to Disentangle the Effects of Frame of Reference and Faking in the Personnel‐Selection Scenario Paradigm","year":2025,"lang":"en","type":"article","venue":"International Journal of Selection and Assessment","topic":"Employer Branding and e-HRM","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Psychology; Selection (genetic algorithm); Personnel selection; Frame (networking); Frame of reference; Applied psychology; Management; Computer science; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005304908,0.0000641383,0.0001227441,0.0002667259,0.00007247856,0.0001218028,0.0001312601,0.00002474,0.000005290514],"category_scores_gemma":[0.0001366738,0.00004018097,0.00003523715,0.0002613855,0.00002455285,0.0002209216,0.00003586431,0.0001641644,1.522815e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004880772,"about_ca_system_score_gemma":0.00003642442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004078129,"about_ca_topic_score_gemma":0.0002405841,"domain_scores_codex":[0.9992315,0.00002496584,0.0003220042,0.00008972089,0.0002662448,0.00006561059],"domain_scores_gemma":[0.999257,0.0001145558,0.0003825868,0.00004745247,0.0001923568,0.000006052938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004704907,0.0004502301,0.8974513,0.0003966173,0.0003806699,0.0000479251,0.001875444,0.000304807,0.01797753,0.05343885,0.002376981,0.02482919],"study_design_scores_gemma":[0.001649361,0.0001898717,0.9680989,0.001447501,0.0001391355,0.0002600651,0.002169662,0.002677364,0.001116956,0.007121332,0.01498741,0.0001423915],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910398,0.0001039806,0.002523875,0.004221998,0.00041003,0.0001271261,3.06617e-7,0.000004346252,0.001568528],"genre_scores_gemma":[0.9991199,0.00005095966,0.0001472567,0.0004469455,0.0001582513,0.000004864307,0.000001105902,0.000003062108,0.00006763028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07064769,"threshold_uncertainty_score":0.1638533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02272932084625563,"score_gpt":0.3211144445183565,"score_spread":0.2983851236721008,"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."}}