{"id":"W4286506316","doi":"10.3233/faia220062","title":"Few-Shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems","year":2022,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; McGill University","funders":"","keywords":"Computer science; Generative grammar; Artificial intelligence; Transformer; Question answering; Natural language processing; Ranking (information retrieval); Similarity (geometry); Generative model; Natural language generation; Natural language; Machine learning; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009821242,0.0003761702,0.000521584,0.0006238632,0.0003594934,0.0003204796,0.000598362,0.0002491059,0.00002979574],"category_scores_gemma":[0.00003817264,0.0004339212,0.0001339969,0.0002365711,0.00009448319,0.0003016337,0.0001639564,0.0005654614,0.00002369092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005888623,"about_ca_system_score_gemma":0.0001203392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001929159,"about_ca_topic_score_gemma":0.00006540324,"domain_scores_codex":[0.9971967,0.00008137005,0.000993779,0.0009833688,0.0003498146,0.000394961],"domain_scores_gemma":[0.9987891,0.0001217408,0.0003660872,0.0004842851,0.0001434845,0.00009527443],"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":[0.00001290304,0.00003895724,0.00004623151,0.00007205018,0.00002080721,0.000003762692,0.00067235,0.009442713,0.0001114609,0.9286926,0.0003113517,0.06057484],"study_design_scores_gemma":[0.00005161481,0.0000958933,0.00000494163,0.0002697902,0.00001958958,0.000008471473,0.0007259689,0.1315512,0.0003943312,0.05636023,0.8099231,0.0005948629],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00003170074,0.003722186,0.9846897,0.0001904737,0.001934599,0.00205623,0.0000269285,0.00008745903,0.00726072],"genre_scores_gemma":[0.09132808,0.0106089,0.09279038,0.0003795764,0.007354818,0.01499845,0.0009014612,0.0004552934,0.7811831],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8918993,"threshold_uncertainty_score":0.9998112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08698854896693997,"score_gpt":0.2978302649463502,"score_spread":0.2108417159794102,"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."}}