{"id":"W4254429661","doi":"10.4018/978-1-5225-7365-4.ch016","title":"Automatic Item Generation","year":2018,"lang":"en","type":"book-chapter","venue":"Advances in educational technologies and instructional design book series","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Test (biology); Process (computing); Item bank; Industrial engineering; Artificial intelligence; Data science; Information retrieval; Machine learning; Item response theory; Engineering; Programming language; Statistics; Mathematics; Psychometrics","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":[0.0001758195,0.0003709397,0.0003098824,0.000562611,0.000291596,0.0001019996,0.0007199195,0.000473623,0.000358364],"category_scores_gemma":[0.0001368705,0.0003688029,0.00005380018,0.0001536345,0.0008975275,0.002674185,0.0002695859,0.0004211851,0.00004751026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375936,"about_ca_system_score_gemma":0.000509459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001009481,"about_ca_topic_score_gemma":0.00001111516,"domain_scores_codex":[0.9981848,0.00002164018,0.0004928221,0.000721127,0.0003318922,0.0002476887],"domain_scores_gemma":[0.9986965,0.0002460781,0.0003173082,0.0005030752,0.0002020294,0.00003498907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003210703,0.00002363644,0.00003812409,0.00002830847,0.00002026549,0.000001542377,0.00003447698,0.00001505945,0.00002729808,0.8818497,0.003119012,0.1148393],"study_design_scores_gemma":[0.00008216436,0.0001111709,0.0001718238,0.0001148772,0.000006540228,0.0001667541,0.000087744,0.0006394289,0.0003224859,0.6736758,0.3243193,0.0003019033],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.003858181,0.2665915,0.1467249,0.1307845,0.01862773,0.004770812,0.0001693727,0.006915591,0.4215574],"genre_scores_gemma":[0.003622197,0.06251897,0.7673329,0.0004524254,0.000770221,0.0006143104,0.0001440697,0.00006330837,0.1644817],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6206079,"threshold_uncertainty_score":0.9998764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134655998604585,"score_gpt":0.2720030772144069,"score_spread":0.250656517228361,"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."}}