{"id":"W2043104383","doi":"10.1007/978-1-4020-4746-6_8","title":"Question Answering By Passage Selection","year":2006,"lang":"en","type":"book-chapter","venue":"Text, speech and language technology","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Question answering; Computer science; Selection (genetic algorithm); Redundancy (engineering); Information retrieval; Data mining; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002029664,0.0004346262,0.0004122391,0.0006980203,0.0001400039,0.0001334791,0.0007766676,0.001103236,0.00005940844],"category_scores_gemma":[0.00004017292,0.0004231769,0.00006402528,0.0002154364,0.000172539,0.0002611473,0.000379827,0.0009621864,0.00003355822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001384536,"about_ca_system_score_gemma":0.00004160967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001799295,"about_ca_topic_score_gemma":0.0001053326,"domain_scores_codex":[0.9982398,0.00001709834,0.0003188595,0.0007776728,0.0002495853,0.0003969743],"domain_scores_gemma":[0.9989731,0.00003135573,0.0002640363,0.0005829865,0.00008574608,0.00006276902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004726857,0.00001961307,0.0000172976,0.00007387368,0.00002558181,0.0002504533,0.00007233574,1.642331e-7,0.01835882,0.2861322,0.02160563,0.6734393],"study_design_scores_gemma":[0.000692442,0.000664542,0.000008962675,0.0007960664,0.0001075188,0.002685488,0.00003919548,0.001130128,0.1921224,0.543506,0.2557893,0.002457822],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001489195,0.1478239,0.6122203,0.003446294,0.0004802365,0.001285531,0.00008098047,0.02134181,0.2118317],"genre_scores_gemma":[0.04277172,0.0005039937,0.4810904,0.0005090921,0.0003224898,0.00005451532,0.0001680256,0.0001734039,0.4744064],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6709815,"threshold_uncertainty_score":0.999822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004151132688285129,"score_gpt":0.2323386379663906,"score_spread":0.2281875052781054,"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."}}