{"id":"W3001060432","doi":"10.5267/j.msl.2019.11.042","title":"Effect of recruitment, selection and culture of organizations on state personnel performance","year":2019,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Socioeconomic Development in MENA","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Business; Organizational culture; State (computer science); Personnel selection; Psychology; Operations management; Knowledge management; Public relations; Management; Computer science; Political science; Engineering; Artificial intelligence; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004782486,0.0001812798,0.000220039,0.0004503499,0.00119035,0.001495966,0.0002823055,0.0002927473,0.002048861],"category_scores_gemma":[0.01008735,0.0001414985,0.0002315853,0.0006883931,0.0009156299,0.0004049954,0.001642496,0.0005241251,0.0002860604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167688,"about_ca_system_score_gemma":0.001979662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005673924,"about_ca_topic_score_gemma":0.01162525,"domain_scores_codex":[0.9957231,0.002639584,0.0001822831,0.000226765,0.0005732231,0.0006549466],"domain_scores_gemma":[0.9876837,0.004079144,0.003665998,0.0006596087,0.001126067,0.002785472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001587291,0.0006118732,0.9775735,0.00001885943,0.00003832251,0.00005318371,0.002774929,0.0001849865,0.0004166079,0.0003126096,0.0002387027,0.01761772],"study_design_scores_gemma":[0.000005182543,0.0002365461,0.9960738,0.00001161043,0.000007591395,0.00001319003,0.002961849,0.0002251326,0.0001117413,0.00005109424,0.0002979603,0.00000421562],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986271,0.00003173601,0.00006124625,0.00008854383,0.000003951782,0.000009556497,0.00001197506,0.000001742317,0.001164316],"genre_scores_gemma":[0.9994766,0.00002362133,0.00005829722,0.00001858329,0.000003865366,0.00001160184,0.00001752281,7.631504e-7,0.0003892665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005673924,"threshold_uncertainty_score":0.02529252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009801512717873056,"score_gpt":0.2720436926206216,"score_spread":0.2622421799027486,"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."}}