{"id":"W2094874816","doi":"10.1145/860435.860534","title":"Passage retrieval vs. document retrieval for factoid question answering","year":2003,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Question answering; Information retrieval; Computer science; Document retrieval; Natural language processing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003674113,0.0007268086,0.001771398,0.003002176,0.001003927,0.002388515,0.001705571,0.001785231,0.04312966],"category_scores_gemma":[0.01742216,0.000265603,0.00120658,0.002171442,0.0008268132,0.004634188,0.001232794,0.001089622,0.009565013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007294954,"about_ca_system_score_gemma":0.0007366661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004693322,"about_ca_topic_score_gemma":0.003495962,"domain_scores_codex":[0.9976484,0.00123073,0.0001611955,0.0003105509,0.0003920262,0.0002571258],"domain_scores_gemma":[0.9891034,0.00892237,0.0002200898,0.0007930209,0.0006509937,0.0003101018],"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":[0.009163329,0.0006287312,0.00285187,0.005270402,0.0004345211,0.0004359191,0.0005854592,0.005915868,0.06172688,0.02738736,0.06138531,0.8242143],"study_design_scores_gemma":[0.002669941,0.009485411,0.02376701,0.002125639,0.004781602,0.005309526,0.002666978,0.4083425,0.1901281,0.1465807,0.2034307,0.0007118505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1805154,0.07357943,0.5940068,0.007450271,0.005223033,0.003599776,0.01035373,0.01561575,0.1096559],"genre_scores_gemma":[0.6740776,0.0142514,0.266142,0.0009884103,0.00194269,0.0008992367,0.01157137,0.0009216969,0.02920563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04312966,"threshold_uncertainty_score":0.1442831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01228187627974468,"score_gpt":0.2841401935360828,"score_spread":0.2718583172563381,"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."}}