{"id":"W2120520504","doi":"10.5815/ijmecs.2015.01.01","title":"Semantic Question Generation Using Artificial Immunity","year":2015,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Topic Modeling","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Sentence; Preprocessor; Artificial intelligence; Natural language processing; Classifier (UML); Set (abstract data type); Test set; Matching (statistics); Semantic role labeling","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":[0.001273657,0.00007143203,0.00008425939,0.000330403,0.0001010633,0.0006090953,0.001003688,0.0000244002,0.000001005223],"category_scores_gemma":[0.00007126633,0.00006643989,0.0000270169,0.0001890607,0.00007787074,0.001706508,0.0002147963,0.000107539,0.000001954956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001851307,"about_ca_system_score_gemma":0.00126077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003700993,"about_ca_topic_score_gemma":0.000003147548,"domain_scores_codex":[0.9985577,0.00006255333,0.0003197914,0.0001821248,0.0007700381,0.0001077412],"domain_scores_gemma":[0.9979163,0.00001577899,0.0002540147,0.0001746175,0.001489682,0.0001496003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006356071,0.0001996288,0.0005953797,0.000002001338,0.00001187187,0.00000456127,0.002726949,0.0206362,0.008917362,0.0757753,0.00007556702,0.8910488],"study_design_scores_gemma":[0.0001111853,0.00003516715,0.0009076375,0.0000284017,0.000003046913,0.0003869358,0.00004032774,0.964445,0.001447556,0.03245091,0.00007361744,0.00007022009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3966047,0.000100713,0.5990261,0.0007932698,0.003416549,0.0000220564,1.041749e-7,0.000008645574,0.00002777528],"genre_scores_gemma":[0.8053064,0.000007182337,0.1935938,0.0003078234,0.0007750774,4.505137e-7,4.360112e-7,0.00000212203,0.000006674457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9438088,"threshold_uncertainty_score":0.587352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08427210239310003,"score_gpt":0.3489781839158917,"score_spread":0.2647060815227917,"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."}}