{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00520961,0.001458078,0.000609271,0.006728197,0.0006106485,0.004425289,0.0010419,0.0006737759,0.003593942],"category_scores_gemma":[0.02043181,0.0002961332,0.0004818382,0.004912941,0.0007652496,0.00433187,0.003039251,0.001017743,0.001725361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001347403,"about_ca_system_score_gemma":0.001497564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00778841,"about_ca_topic_score_gemma":0.005235252,"domain_scores_codex":[0.9959329,0.00160825,0.0002881568,0.0008499715,0.001039133,0.0002817008],"domain_scores_gemma":[0.9871952,0.008167495,0.001377193,0.0010371,0.001842143,0.000380905],"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":[0.0004914007,0.0007704549,0.2179062,0.001119006,0.0002386193,0.0004062227,0.01172326,0.05596657,0.004411523,0.02088054,0.01943593,0.6666502],"study_design_scores_gemma":[0.00008214761,0.0009746441,0.1846664,0.0009113587,0.00014071,0.0002627673,0.01715358,0.6154451,0.01124763,0.1146598,0.05413665,0.0003190645],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5045921,0.002285745,0.3863958,0.005989071,0.0005244873,0.001438186,0.01126016,0.01334223,0.07417221],"genre_scores_gemma":[0.9194538,0.0006382681,0.07155713,0.0001636237,0.0001246648,0.0003638851,0.004732484,0.0003127159,0.002653539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00778841,"threshold_uncertainty_score":0.02755135,"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."}}