{"id":"W2296508364","doi":"","title":"Optimizing Question-Answering Systems Using Genetic Algorithms","year":2015,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Lakehead University; Université Laval","funders":"","keywords":"Adaptability; Sequence (biology); Computer science; Question answering; Genetic algorithm; Algorithm; Space (punctuation); Artificial intelligence; Machine learning; Theoretical computer science","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":[0.005471491,0.0001515826,0.0001790664,0.0000607523,0.0006415097,0.000746232,0.001729674,0.00009714762,0.000002388696],"category_scores_gemma":[0.0001502776,0.0001148215,0.0001148864,0.0007411131,0.0001574177,0.0005065916,0.001014547,0.0007329881,0.00004258107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004610346,"about_ca_system_score_gemma":0.0004691246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001125395,"about_ca_topic_score_gemma":0.000002412343,"domain_scores_codex":[0.9965476,0.000495054,0.0002854011,0.0004773508,0.00141439,0.000780246],"domain_scores_gemma":[0.9977678,0.0002235883,0.00005345881,0.00109348,0.0006020396,0.000259627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000615764,0.00003541942,0.0003081211,0.00008804042,0.00009495587,0.00003728743,0.02545085,0.9383436,0.00223339,0.01975653,0.005219702,0.008425933],"study_design_scores_gemma":[0.0001953025,0.00002973408,0.00003501827,0.0000584561,0.000004015196,0.00003709871,0.001079793,0.9954943,0.0002327108,0.001153082,0.001542862,0.0001376453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03549364,0.001606684,0.9595488,0.001290671,0.001248907,0.000346842,0.000001084499,0.0001849866,0.0002783962],"genre_scores_gemma":[0.4916974,0.0001194777,0.5049929,0.0002242724,0.002138657,0.00007488157,0.000001215803,0.00004081828,0.0007103137],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4562038,"threshold_uncertainty_score":0.7195932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1765017249053866,"score_gpt":0.3937401107580525,"score_spread":0.2172383858526659,"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."}}