{"id":"W4404396740","doi":"10.56294/dm2025469","title":"Design and Implementation of an Adaptive Tutoring System for Enhanced E-Learning","year":2024,"lang":"en","type":"article","venue":"Data & Metadata","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Multimedia; Human–computer interaction; Computer architecture","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":[0.00111274,0.0004751174,0.0004614259,0.0004175734,0.0005102983,0.001305815,0.001800326,0.001640375,0.003816353],"category_scores_gemma":[0.002080352,0.0003307125,0.000391537,0.0001506191,0.0004427421,0.0008598701,0.0009515401,0.0007466876,0.001125777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004958719,"about_ca_system_score_gemma":0.001149279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001012858,"about_ca_topic_score_gemma":0.0007582547,"domain_scores_codex":[0.9990866,0.0002634171,0.00009901795,0.0001972051,0.0002531743,0.0001005798],"domain_scores_gemma":[0.9990977,0.0002170165,0.00006966654,0.0001027796,0.0003624032,0.0001503929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00112054,0.002304584,0.01101345,0.001168756,0.0001681439,0.002009026,0.003199411,0.08044598,0.4370289,0.01394966,0.005184651,0.4424069],"study_design_scores_gemma":[0.0005357617,0.003791657,0.007711566,0.0001162315,0.000252052,0.0008683268,0.0005622061,0.674567,0.2426182,0.002401208,0.06643303,0.0001427332],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1162587,0.0001640342,0.8670484,0.0003413183,0.0001934489,0.001942687,0.0001083844,0.005553553,0.008389291],"genre_scores_gemma":[0.5409648,0.0001188163,0.4492821,0.0001741559,0.00002870769,0.001344751,0.0001377683,0.0001989877,0.007749964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003816353,"threshold_uncertainty_score":0.01276702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08200156943109914,"score_gpt":0.3440427567272941,"score_spread":0.2620411872961949,"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."}}