{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001046371,0.00008899045,0.00008873991,0.00005200792,0.00007991348,0.000113267,0.0004616838,0.00002246972,0.00002055727],"category_scores_gemma":[0.000009354373,0.00006252162,0.00001675659,0.0001889342,0.00001366074,0.0005662433,0.00006319887,0.00008579828,0.00001657365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002193935,"about_ca_system_score_gemma":0.00003533539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001859484,"about_ca_topic_score_gemma":0.000008186373,"domain_scores_codex":[0.9992347,0.00001872003,0.0000994565,0.00029397,0.0001489219,0.00020423],"domain_scores_gemma":[0.9994945,0.00002370918,0.00003173192,0.0003531065,0.00005282832,0.00004414613],"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":[0.000008513084,0.00003763425,0.0003913077,0.000005915276,0.000007637947,0.000006869347,0.002851532,0.001128919,0.0006085598,0.6731995,0.0001098373,0.3216438],"study_design_scores_gemma":[0.001789977,0.0008063721,0.03198773,0.0004047251,0.00002442024,0.00006966939,0.0005892177,0.7638471,0.04783339,0.1483865,0.002930453,0.001330528],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01119628,0.00002804057,0.9281259,0.001010169,0.0000607378,0.00008070302,8.223869e-8,0.000227524,0.05927056],"genre_scores_gemma":[0.8096145,0.000001817243,0.188749,0.000530045,0.00002567385,0.00000235158,2.383122e-7,0.000002354029,0.001073975],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7984183,"threshold_uncertainty_score":0.2549558,"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."}}