{"id":"W2126620235","doi":"","title":"Dialogue Systems for Language Learning","year":2013,"lang":"es","type":"article","venue":"IE Comunicaciones: Revista Iberoamericana de Informática Educativa","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Waterloo","funders":"","keywords":"Computer science; Dialog box; Conversation; Language industry; Grammar; Foreign language; Comprehension approach; Vocabulary; Natural language; Natural language processing; Universal Networking Language; Language technology; Language acquisition; Bridging (networking); Linguistics; Artificial intelligence; World Wide Web","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":[0.00248005,0.0009441364,0.0009173222,0.001371671,0.001626034,0.006469843,0.001396573,0.002807604,0.01717718],"category_scores_gemma":[0.005786956,0.0004198078,0.0007811874,0.001264319,0.003814586,0.007515907,0.003788424,0.002736575,0.004170363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001807178,"about_ca_system_score_gemma":0.001084501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002058156,"about_ca_topic_score_gemma":0.001076336,"domain_scores_codex":[0.9972613,0.001461425,0.0001937946,0.0004760664,0.000461,0.0001464623],"domain_scores_gemma":[0.9973272,0.001819117,0.0001187472,0.0003630613,0.0002510924,0.0001207251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005031432,0.00003599687,0.0002020955,0.0005125355,0.00003773332,0.0001547977,0.001104271,0.003057843,0.001075525,0.8817616,0.01276695,0.09924033],"study_design_scores_gemma":[0.00003007574,0.00004711559,0.0002086448,0.0002940604,0.00002580921,0.0003289774,0.000460657,0.01744991,0.0007541903,0.7184052,0.2619555,0.0000400117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006509353,0.08404648,0.7545232,0.012126,0.003497739,0.0003414968,0.00064665,0.002600204,0.1357089],"genre_scores_gemma":[0.420925,0.04335389,0.458015,0.00325191,0.004647882,0.001219133,0.001908216,0.000788712,0.06589015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01717718,"threshold_uncertainty_score":0.05746335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01574765758184029,"score_gpt":0.2756735919831672,"score_spread":0.2599259344013269,"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."}}