{"id":"W4408954532","doi":"10.47392/irjaem.2025.0140","title":"Learnova: An Intelligent LMS for Personalized Education and Comprehensive Management","year":2025,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering and Management (IRJAEM)","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Learning Management; Computer science; Knowledge management; Engineering management; Multimedia; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005402996,0.0001322113,0.0001131029,0.0008961002,0.0002450139,0.000270825,0.0005494401,0.00003843819,0.000007063882],"category_scores_gemma":[0.00005091264,0.0001278018,0.00003674064,0.0002696841,0.00005636962,0.0003611764,0.0002668402,0.0003196786,0.000003847995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002058088,"about_ca_system_score_gemma":0.00004586127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001291133,"about_ca_topic_score_gemma":4.759016e-7,"domain_scores_codex":[0.9987403,0.00003558084,0.0002126867,0.000347106,0.0004055975,0.0002587483],"domain_scores_gemma":[0.9991702,0.0001643251,0.00004848869,0.0001957309,0.0003172549,0.0001039724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003106955,0.0001544822,0.00002541527,0.00007775198,0.0001354866,0.000007812058,0.00005195914,0.001850775,0.0001326559,0.7525809,0.001109495,0.2438422],"study_design_scores_gemma":[0.001167037,0.0002880714,0.004710868,0.0005938386,0.00001641691,0.0000410856,0.001329868,0.0274995,0.0004252839,0.07384412,0.8898496,0.0002342984],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03976209,0.001905787,0.9255074,0.01881911,0.002858522,0.001052615,0.000004212045,0.0001563597,0.009933888],"genre_scores_gemma":[0.5569807,0.01709091,0.389371,0.001421929,0.0002917551,0.0008046103,0.00003068123,0.00003470295,0.03397373],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8887401,"threshold_uncertainty_score":0.5211606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03794340351437669,"score_gpt":0.414924323172027,"score_spread":0.3769809196576503,"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."}}