{"id":"W7062375546","doi":"","title":"Understanding Employee Attrition Factors in the Information Technology Sector: A Text Analytics Perspective","year":2023,"lang":"en","type":"other","venue":"Brock University Digital Repository (Brock University)","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Attrition; Latent Dirichlet allocation; Perspective (graphical); Seekers; Topic model; Sentiment analysis; Analytics; Polarity (international relations); Information technology","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":[0.004408895,0.0003555894,0.000481965,0.004158822,0.001131576,0.003215931,0.0005113683,0.0009699307,0.001239737],"category_scores_gemma":[0.01513922,0.0002216519,0.0005041519,0.003237389,0.0007284162,0.003249156,0.001196075,0.000934821,0.000357205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001410064,"about_ca_system_score_gemma":0.001040329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006760175,"about_ca_topic_score_gemma":0.00567498,"domain_scores_codex":[0.9977171,0.0009008624,0.000228214,0.0002204032,0.0005760561,0.0003573268],"domain_scores_gemma":[0.9744999,0.01765087,0.004608284,0.0003206507,0.002149093,0.0007710839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000191605,0.0004002022,0.88157,0.0003152583,0.00007194436,0.0004694985,0.03214686,0.0009279608,0.001784953,0.00190606,0.001460862,0.07875464],"study_design_scores_gemma":[0.00001450371,0.0002860755,0.8729084,0.0002918167,0.0001009924,0.0003068097,0.08593587,0.02942176,0.001284879,0.003503185,0.005882502,0.00006314796],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904585,0.000765025,0.004646299,0.001685256,0.00002077125,0.00005078033,0.0003175866,0.00002564328,0.00203014],"genre_scores_gemma":[0.9974336,0.0002745325,0.001423149,0.0001251273,0.00004922716,0.00003557791,0.0002758034,0.000007455197,0.0003754784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006760175,"threshold_uncertainty_score":0.02331674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027633534417204,"score_gpt":0.2050972121720198,"score_spread":0.1748208768278477,"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."}}