{"id":"W2013181170","doi":"10.1109/iri.2010.5558906","title":"Sentence level fact based search engine: News Fact Finder","year":2010,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Substring; Computer science; Search engine; Sentence; Information retrieval; The Internet; Matching (statistics); Suffix; Order (exchange); World Wide Web; Artificial intelligence; Data structure; Mathematics; Programming language","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":[0.0001898209,0.0001436847,0.0001181525,0.00008569552,0.0001380272,0.0002277814,0.00112504,0.00007793222,0.0005282229],"category_scores_gemma":[0.00003526494,0.0001038303,0.00005661133,0.000224609,0.00003379911,0.0006423814,0.0004059123,0.0003529957,0.0002976859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001119862,"about_ca_system_score_gemma":0.0001298791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005320157,"about_ca_topic_score_gemma":0.00007614237,"domain_scores_codex":[0.9986571,0.0000306888,0.0001499084,0.0004235414,0.0003992435,0.00033949],"domain_scores_gemma":[0.9986872,0.0001195366,0.00002878662,0.0009052731,0.00008418114,0.0001749956],"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":[0.00001242012,0.0003224534,0.007208264,0.00002667875,0.00001977678,0.00006802865,0.0003138964,0.0009861195,0.05194635,0.01283598,0.0367271,0.8895329],"study_design_scores_gemma":[0.0004107947,0.0000471744,0.02804337,0.00001034224,0.00000165367,0.00001279454,0.00002388526,0.9255716,0.02460643,0.0003173288,0.02066698,0.000287717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0193979,0.000006912959,0.9765307,0.00141613,0.0005182059,0.0001065364,0.00001659673,0.0001831094,0.001823863],"genre_scores_gemma":[0.6363735,0.000003542056,0.3610135,0.0008281477,0.0001018888,0.000005570516,0.00001520383,0.00000969367,0.001648936],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9245854,"threshold_uncertainty_score":0.5783671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04552391365676987,"score_gpt":0.2801020250425687,"score_spread":0.2345781113857988,"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."}}