{"id":"W4245889339","doi":"10.5465/ambpp.2019.18018abstract","title":"A Critical Review of Algorithms in HRM: Definition, Theory, and Practice","year":2019,"lang":"en","type":"review","venue":"Academy of Management Proceedings","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Heuristics; Analytics; Computer science; Human resource management; Data science; Algorithm; Commercialization; Knowledge management; Business; Marketing","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003052544,0.0004072228,0.001640579,0.0008556792,0.00004318921,0.00007665077,0.0006880458,0.0003620452,0.00006402787],"category_scores_gemma":[0.002627835,0.0003459416,0.0002059578,0.001050988,0.0002572798,0.00156574,0.0009547931,0.0005387864,0.0000697715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003087034,"about_ca_system_score_gemma":0.00001198162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006908786,"about_ca_topic_score_gemma":6.357617e-8,"domain_scores_codex":[0.9975443,0.00002162105,0.00111847,0.0005505679,0.0004350753,0.0003299664],"domain_scores_gemma":[0.998013,0.0005065359,0.001172301,0.0001280464,0.0001696634,0.00001050556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006551523,0.00003536082,0.000003402444,0.3020181,0.00005616304,0.000001294429,0.000003563544,2.261531e-9,4.24514e-8,0.4033664,0.003848856,0.2906603],"study_design_scores_gemma":[0.0001510662,0.00001287636,0.00001666569,0.1371762,0.002095051,0.000009398209,0.0002447712,0.000001617711,3.015047e-7,0.02527263,0.8347408,0.0002787292],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000154748,0.9194451,0.00002130044,0.002033472,0.00005071332,0.001294103,0.00000438603,0.0000849092,0.0770645],"genre_scores_gemma":[0.00002391769,0.9955566,0.001629139,0.002280509,0.0001225778,0.0001563006,0.00001212984,0.00004681406,0.0001720066],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8308918,"threshold_uncertainty_score":0.9998993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138671877591147,"score_gpt":0.3660346510944159,"score_spread":0.2521674633353012,"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."}}