{"id":"W4403582513","doi":"10.1145/3627673.3679912","title":"Enhanced Retrieval Effectiveness through Selective Query Generation","year":2024,"lang":"en","type":"article","venue":"","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"","keywords":"Computer science; Query expansion; Query optimization; Web search query; Information retrieval; Sargable; Search engine","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":[0.003717141,0.001150269,0.001635971,0.001856835,0.0004325144,0.001514565,0.001792026,0.0009521957,0.002929079],"category_scores_gemma":[0.01246295,0.0003073115,0.0008401317,0.001558517,0.0008654988,0.003260861,0.001488107,0.001077104,0.001582219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000794727,"about_ca_system_score_gemma":0.001408823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002506122,"about_ca_topic_score_gemma":0.003264759,"domain_scores_codex":[0.9965883,0.001172272,0.0003066562,0.0004910054,0.001164418,0.0002773197],"domain_scores_gemma":[0.9952424,0.002349058,0.0003486996,0.001112175,0.000830473,0.0001173004],"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":[0.001712168,0.001180447,0.006134985,0.001251212,0.0002395723,0.0003551695,0.0005547883,0.06674317,0.1462567,0.01338784,0.01925848,0.7429254],"study_design_scores_gemma":[0.0004360297,0.001893319,0.004121518,0.00006131124,0.00041086,0.001051562,0.0004029139,0.84264,0.1187438,0.01304934,0.01703189,0.0001575123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3274075,0.008748597,0.6373383,0.001378107,0.0001712155,0.001198721,0.00177369,0.00961199,0.01237199],"genre_scores_gemma":[0.7413524,0.001518778,0.249921,0.0004920734,0.0001562501,0.0002677776,0.002707694,0.0003963555,0.003187766],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003717141,"threshold_uncertainty_score":0.01965833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02846886968593564,"score_gpt":0.3057315642998132,"score_spread":0.2772626946138776,"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."}}