{"id":"W2155925704","doi":"10.3115/1609067.1609141","title":"Flexible answer typing with discriminative preference ranking","year":2009,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Discriminative model; Ranking (information retrieval); Preference; Computer science; Artificial intelligence; Typing; Information retrieval; Natural language processing; Machine learning; Statistics; Mathematics; Speech recognition","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":[0.004402206,0.001330274,0.00192376,0.002490695,0.000628671,0.001597967,0.002092334,0.001739078,0.003845367],"category_scores_gemma":[0.01729913,0.000472424,0.001072947,0.002516308,0.0005620597,0.003550265,0.001585735,0.002093715,0.003290361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005844187,"about_ca_system_score_gemma":0.001004898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002254169,"about_ca_topic_score_gemma":0.004659124,"domain_scores_codex":[0.9943645,0.00277814,0.0003185628,0.001076395,0.001090698,0.0003718484],"domain_scores_gemma":[0.9879957,0.006353225,0.0007704646,0.002411663,0.002062091,0.0004068952],"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":[0.0007715215,0.0005474359,0.005469006,0.0003748477,0.0001333994,0.0001726327,0.0003177809,0.03147829,0.02535574,0.006795563,0.01232403,0.9162597],"study_design_scores_gemma":[0.00008788596,0.000349054,0.002864997,0.00003326099,0.00006792189,0.0004494038,0.0001446537,0.9486352,0.01571557,0.02681939,0.004720873,0.0001117876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03681551,0.0005079065,0.9549574,0.0002330625,0.00006943692,0.0001922534,0.0004104352,0.004863408,0.001950752],"genre_scores_gemma":[0.5756209,0.0002697567,0.4159697,0.0003655452,0.0002126425,0.0003251376,0.002186538,0.0003808275,0.004668923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004402206,"threshold_uncertainty_score":0.02328134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05204338636515513,"score_gpt":0.2595056353299653,"score_spread":0.2074622489648102,"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."}}