{"id":"W803028973","doi":"","title":"Generating Natural Language Questions to Support Learning On-Line","year":2013,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Natural language; Context (archaeology); Task (project management); Natural language processing; Artificial intelligence; Natural language understanding; Question answering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003253278,0.001116138,0.0005587565,0.0009590121,0.0004083169,0.001617548,0.002601669,0.002107484,0.009669248],"category_scores_gemma":[0.01573413,0.0003809326,0.0007368744,0.0005965133,0.0005143047,0.002826259,0.001374725,0.001320009,0.006420213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006371639,"about_ca_system_score_gemma":0.0009914148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001143835,"about_ca_topic_score_gemma":0.001802529,"domain_scores_codex":[0.9970866,0.001505493,0.0002233933,0.0005128962,0.0005714659,0.0001002403],"domain_scores_gemma":[0.9838766,0.01047724,0.0009654398,0.002171622,0.002188853,0.0003202746],"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":[0.0004712585,0.001417519,0.007133122,0.001215805,0.00009506108,0.001105719,0.002283238,0.01997732,0.1142256,0.01805481,0.04257487,0.7914456],"study_design_scores_gemma":[0.0002725701,0.00071039,0.006399485,0.0002594449,0.0001154739,0.001519779,0.0007649049,0.5368525,0.235082,0.05475404,0.1630666,0.0002028419],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02485595,0.0001388721,0.9245234,0.0005402515,0.0001107586,0.000656373,0.001404406,0.04155922,0.006210795],"genre_scores_gemma":[0.1177859,0.0001560395,0.8693798,0.000231663,0.00006289611,0.000375704,0.005647841,0.001139657,0.005220518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009669248,"threshold_uncertainty_score":0.03234684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357308826360467,"score_gpt":0.3014155889024207,"score_spread":0.287842500638816,"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."}}