{"id":"W4408151458","doi":"10.3991/ijac.v18i1.53121","title":"Leveraging Analytics to Drive Human Performance","year":2025,"lang":"en","type":"article","venue":"International Journal of Advanced Corporate Learning (iJAC)","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of National Defence","funders":"","keywords":"Analytics; Computer science; Data science; Process management; Knowledge management; Human–computer interaction; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000281172,0.0001508913,0.0002232495,0.0009446942,0.0001872447,0.0002586176,0.0007246778,0.00005234457,0.00005681366],"category_scores_gemma":[0.0003147052,0.0001409059,0.00009358703,0.0005112197,0.00004911735,0.0009851044,0.000269227,0.0004676872,0.00006400231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001211925,"about_ca_system_score_gemma":0.00004329092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001134139,"about_ca_topic_score_gemma":0.00000487212,"domain_scores_codex":[0.9987856,0.000007733757,0.0004620863,0.0001644074,0.0003891142,0.0001910505],"domain_scores_gemma":[0.9978371,0.00003666506,0.0009453153,0.0001124773,0.001054542,0.00001395485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004003671,0.0001355681,0.3581268,0.00009066177,0.0004490597,0.0002575371,0.0002274363,0.3834774,0.02001332,0.04303046,0.005197821,0.1885936],"study_design_scores_gemma":[0.004438045,0.0003702917,0.2465765,0.002456001,0.0002421267,0.00007309199,0.00487851,0.02242763,0.008627256,0.07473435,0.6339704,0.001205751],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765787,0.00005845588,0.009761972,0.003519722,0.001042349,0.00007021517,3.738316e-7,0.0001026035,0.008865638],"genre_scores_gemma":[0.9942474,0.00003905788,0.001801463,0.001318324,0.0005153939,0.000002395874,0.000005730217,0.00001523226,0.002054948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6287726,"threshold_uncertainty_score":0.5745978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02610522378380628,"score_gpt":0.2687809352423605,"score_spread":0.2426757114585542,"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."}}