{"id":"W2885711770","doi":"","title":"Comparison of Two Interactive Search Refinement Techniques","year":2004,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Information retrieval; Set (abstract data type); Query expansion; Document retrieval; Web search query; Noun phrase; Natural language processing; Search engine; Artificial intelligence; Noun; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003400648,0.001424733,0.001312232,0.001891678,0.0006851507,0.001398167,0.003839727,0.00166883,0.009175998],"category_scores_gemma":[0.01954108,0.0006026148,0.00136617,0.002010991,0.0008896294,0.003608762,0.002518918,0.00188052,0.00248659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007659131,"about_ca_system_score_gemma":0.001079349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006214433,"about_ca_topic_score_gemma":0.006979879,"domain_scores_codex":[0.9946616,0.002063318,0.0003918545,0.0004061692,0.0021263,0.0003508262],"domain_scores_gemma":[0.9850017,0.0103849,0.0004767026,0.002244155,0.001673617,0.0002187817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003930146,0.001323125,0.002594244,0.001113281,0.0003245065,0.0002449391,0.002245245,0.05230336,0.03061257,0.02286326,0.007029778,0.8754156],"study_design_scores_gemma":[0.00147139,0.00283707,0.004581946,0.0002326467,0.0005928137,0.00118231,0.001371602,0.861446,0.06514808,0.01720309,0.04360303,0.000330004],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05889498,0.002069091,0.9172341,0.0003441946,0.00007429269,0.0006358977,0.0002756859,0.009244183,0.01122747],"genre_scores_gemma":[0.3195442,0.001268828,0.666012,0.0003382672,0.00009250452,0.0006105439,0.001309386,0.001579543,0.00924465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009175998,"threshold_uncertainty_score":0.03069675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0320002516061259,"score_gpt":0.4021493232363351,"score_spread":0.3701490716302092,"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."}}