{"id":"W2578302695","doi":"10.1109/wi.2016.0095","title":"Context Free Frequently Asked Questions Detection Using Machine Learning Techniques","year":2016,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Fredericton","funders":"","keywords":"Computer science; Frequently asked questions; Naive Bayes classifier; Classifier (UML); Artificial intelligence; Information retrieval; Machine learning; Natural language processing; Support vector machine; Feature engineering; Parsing","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":[0.002689307,0.001194748,0.001057464,0.007084907,0.0008537763,0.001433667,0.001237007,0.001832495,0.001465028],"category_scores_gemma":[0.009217928,0.0003067805,0.001475006,0.003003325,0.0003764302,0.002206593,0.001081432,0.001261005,0.001306381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006690192,"about_ca_system_score_gemma":0.0008019712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003262172,"about_ca_topic_score_gemma":0.00385222,"domain_scores_codex":[0.9959645,0.001296716,0.0004521066,0.001047767,0.0009117028,0.0003271782],"domain_scores_gemma":[0.9916428,0.004810142,0.001040078,0.0005644616,0.001679439,0.0002630411],"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":[0.0005975601,0.0008482094,0.05127933,0.0008044689,0.000323112,0.001349938,0.001555859,0.01595602,0.06182259,0.004369969,0.01621304,0.84488],"study_design_scores_gemma":[0.00006155197,0.0005112102,0.07016423,0.0001408176,0.0002006304,0.002225151,0.001499362,0.8500414,0.0387424,0.014415,0.02181792,0.0001803172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2339029,0.003920726,0.7441707,0.0007552219,0.0003018021,0.000879151,0.003914622,0.008893332,0.003261593],"genre_scores_gemma":[0.7091119,0.0006508373,0.2803584,0.0002410533,0.0003233028,0.0005748312,0.006025199,0.0001282058,0.002586318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007084907,"threshold_uncertainty_score":0.01422256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02752615980495196,"score_gpt":0.2582787823248984,"score_spread":0.2307526225199465,"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."}}