{"id":"W3201316946","doi":"10.1017/iop.2021.79","title":"“I” feel(s) left out: The importance of information and communication technology in personnel selection research","year":2021,"lang":"en","type":"article","venue":"Industrial and Organizational Psychology","topic":"Employer Branding and e-HRM","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Selection (genetic algorithm); Psychology; Computer science; Artificial intelligence","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":[0.06022428,0.0002487046,0.000582727,0.002105532,0.005512499,0.01359142,0.0009409873,0.00444012,0.01040126],"category_scores_gemma":[0.1560379,0.0005331254,0.000365581,0.003211326,0.01260459,0.01343541,0.002937914,0.006811892,0.002916267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002307007,"about_ca_system_score_gemma":0.004335821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005413186,"about_ca_topic_score_gemma":0.007571194,"domain_scores_codex":[0.9543628,0.03850632,0.0009153182,0.001364958,0.003859387,0.0009912966],"domain_scores_gemma":[0.8381512,0.1323392,0.005878493,0.0035632,0.01506407,0.005003864],"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":[0.0002374778,0.0001350454,0.04706438,0.001332115,0.0001657463,0.0006019332,0.188531,0.000154202,0.000954271,0.04214633,0.3791333,0.3395442],"study_design_scores_gemma":[0.0001001021,0.0003124193,0.07962552,0.00946771,0.0002240433,0.002671481,0.5413195,0.001312366,0.001124408,0.09236287,0.2711427,0.0003368742],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06597742,0.01259438,0.008250117,0.8698431,0.006608647,0.00005246827,0.0001494746,0.0001404058,0.03638398],"genre_scores_gemma":[0.7519534,0.01747319,0.005534444,0.2070531,0.00668568,0.0002335218,0.0001179281,0.0002178076,0.01073097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06022428,"threshold_uncertainty_score":0.3185002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07626210580591998,"score_gpt":0.3214349949540172,"score_spread":0.2451728891480972,"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."}}