{"id":"W4405442077","doi":"10.3390/app142411750","title":"From Recruitment to Retention: AI Tools for Human Resource Decision-Making","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"Onboarding; Computer science; Analytics; Documentation; Personalization; Knowledge management; Data science; Psychology; World Wide Web","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":[0.01667838,0.0006495304,0.0005725572,0.002582979,0.00217461,0.01036324,0.001980616,0.001874836,0.008638107],"category_scores_gemma":[0.04733233,0.0003733679,0.0006577226,0.002424185,0.004029321,0.008725828,0.004644589,0.002983931,0.002063604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002296998,"about_ca_system_score_gemma":0.005214728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003088919,"about_ca_topic_score_gemma":0.002690152,"domain_scores_codex":[0.9899873,0.007287004,0.0003937861,0.0005778819,0.001438385,0.000315612],"domain_scores_gemma":[0.9578,0.03320125,0.002108576,0.002690058,0.002881215,0.001318978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000291124,0.0004611975,0.01074061,0.0006577379,0.00009524068,0.0002395943,0.006685897,0.01687644,0.001220624,0.2566023,0.01977158,0.6863576],"study_design_scores_gemma":[0.000106041,0.0003760402,0.005527341,0.001451772,0.00009002142,0.0002262366,0.007730789,0.0809325,0.002198829,0.7687278,0.1324529,0.0001797184],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06660535,0.008943342,0.6587635,0.08644749,0.001157444,0.0007757863,0.000438356,0.002658207,0.1742106],"genre_scores_gemma":[0.6497213,0.004429277,0.3255869,0.003929725,0.0007490275,0.0006371943,0.0003208457,0.0002211405,0.01440459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01667838,"threshold_uncertainty_score":0.08820474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1219909297000671,"score_gpt":0.3495166410801659,"score_spread":0.2275257113800988,"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."}}