{"id":"W4393979635","doi":"10.53555/sfs.v8i3.2437","title":"Investigating Employee Retention in IT Companies: A Study in India","year":2022,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Employee retention; Business; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00711568,0.0000945742,0.0002618241,0.001060155,0.0002114745,0.0002628823,0.0006500597,0.00002722568,0.00008752264],"category_scores_gemma":[0.001159465,0.00008286467,0.00002918897,0.002878072,0.0002398938,0.001694232,0.0003665475,0.0004123359,0.000001536472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008938037,"about_ca_system_score_gemma":0.00007448356,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005011992,"about_ca_topic_score_gemma":0.01816881,"domain_scores_codex":[0.9983252,0.0001362638,0.0006356363,0.0001624318,0.0005157634,0.0002247006],"domain_scores_gemma":[0.9992048,0.0001604756,0.000483334,0.00007897829,0.00006640971,0.00000599721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001644228,0.0001096113,0.9970054,0.0000114363,0.000002433576,0.00003281559,0.001036265,0.0006004388,0.00001860841,0.00008252339,0.0007140492,0.0003699475],"study_design_scores_gemma":[0.0003915934,0.0001333527,0.9532422,0.00004476618,0.000002112706,0.000002945008,0.04336719,0.000167275,0.000001462458,0.002295975,0.0002574971,0.00009362039],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973891,0.00005511372,0.000001584124,0.0008197077,0.0003083792,0.0001376039,0.000001086024,0.00001477415,0.001272684],"genre_scores_gemma":[0.9995425,0.000006365716,0.00009901914,0.0002761649,0.00004300651,0.000009564446,0.000001164425,0.00000488341,0.00001731544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04376322,"threshold_uncertainty_score":0.999747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.241223552683606,"score_gpt":0.2899697847852367,"score_spread":0.04874623210163065,"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."}}