{"id":"W1549048100","doi":"","title":"VisiQ: Supporting visual and interactive query refinement","year":2007,"lang":"en","type":"article","venue":"Web Intelligence and Agent Systems An International Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Query expansion; Information retrieval; Web query classification; Query language; Query optimization; Web search query; Sargable; Spatial query; Process (computing); Representation (politics); Information needs; Search engine; World Wide Web","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":[0.005053555,0.002158754,0.001584102,0.003663228,0.0006567408,0.003666876,0.003915789,0.001652091,0.02466974],"category_scores_gemma":[0.01990911,0.00116547,0.001382794,0.002185199,0.001116274,0.004950208,0.008626572,0.001950041,0.006158967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009376768,"about_ca_system_score_gemma":0.001112085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007220673,"about_ca_topic_score_gemma":0.006013136,"domain_scores_codex":[0.9968607,0.00076695,0.0002858829,0.0004603703,0.00138216,0.0002438853],"domain_scores_gemma":[0.9909803,0.005867087,0.0003317084,0.001468758,0.0009556593,0.0003963349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006928042,0.0008579251,0.004551175,0.0022793,0.0003162472,0.001687134,0.00427298,0.01679516,0.06432781,0.03351277,0.2323653,0.6321062],"study_design_scores_gemma":[0.00202359,0.0008152857,0.003864765,0.0005201118,0.0002600271,0.001175405,0.001380419,0.5213127,0.07488669,0.070866,0.3223659,0.0005290923],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0167127,0.0006669361,0.6026661,0.0005188049,0.0001541014,0.001088929,0.005855059,0.3589596,0.01337782],"genre_scores_gemma":[0.2250295,0.0008960644,0.7249777,0.000933008,0.0001932681,0.001616151,0.01852753,0.01506589,0.01276094],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02466974,"threshold_uncertainty_score":0.08252847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03351170831330354,"score_gpt":0.3732770120426175,"score_spread":0.339765303729314,"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."}}