{"id":"W4413052386","doi":"10.1109/tvcg.2025.3596541","title":"More Like Vis, Less Like Vis: Comparing Interactions for Integrating User Preferences Into Partial Specification Recommenders","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visualization; Computer science; Data visualization; Process (computing); Human–computer interaction; Interactive visualization; Comprehension; Creative visualization; Data mining; Information retrieval; Machine learning; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002654993,0.0002986938,0.0003009989,0.0007399414,0.0007794212,0.0007051075,0.0005077455,0.0001216118,0.000009439099],"category_scores_gemma":[0.000008343601,0.0003033301,0.0001362567,0.001289988,0.000103673,0.0008865378,0.00001996908,0.0002479797,0.000003019197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006432461,"about_ca_system_score_gemma":0.00008941928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003683749,"about_ca_topic_score_gemma":0.0001841404,"domain_scores_codex":[0.9980131,0.0001548482,0.000610779,0.0006619215,0.0002955269,0.0002637922],"domain_scores_gemma":[0.9986696,0.0002084911,0.0002047478,0.0004522431,0.0003406732,0.0001242142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005613042,0.0007571147,0.0004960531,0.000171879,0.0001926394,7.510019e-7,0.004115591,0.002093738,0.00004954393,0.9416284,0.005380029,0.04505812],"study_design_scores_gemma":[0.0006426722,0.000115612,0.0001650941,0.0002046752,0.00005653968,0.000002769278,0.0006889171,0.9729823,0.0009964892,0.0009517646,0.0228898,0.0003033573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002586262,0.00002986632,0.994159,0.0004544526,0.001901455,0.000410094,0.00001490387,0.0003486864,0.00009529215],"genre_scores_gemma":[0.9815886,0.0003745331,0.01384852,0.003564699,0.00009505011,0.0001236898,0.0001238578,0.00002806473,0.0002530058],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9803104,"threshold_uncertainty_score":0.9999419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05653016292367945,"score_gpt":0.3423513509854848,"score_spread":0.2858211880618053,"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."}}