{"id":"W2036433269","doi":"10.1145/985692.985704","title":"A comparison of static, adaptive, and adaptable menus","year":2004,"lang":"en","type":"article","venue":"","topic":"Usability and User Interface Design","field":"Computer Science","cited_by":285,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Personalization; Computer science; Control (management); Human–computer interaction; Software; Interface (matter); User interface; World Wide Web; Artificial intelligence; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001328432,0.00006295805,0.0001468158,0.00003183513,0.000032182,0.00003311498,0.0002527083,0.00002371994,0.00002133525],"category_scores_gemma":[0.00001499543,0.00005327938,0.00001730173,0.000118094,0.00005206578,0.0002705559,0.00009935852,0.00005229797,0.00001485859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001716306,"about_ca_system_score_gemma":0.00004129529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002164467,"about_ca_topic_score_gemma":0.00005750842,"domain_scores_codex":[0.9993887,0.00002447795,0.0001651452,0.0001716096,0.0001282558,0.0001218337],"domain_scores_gemma":[0.9995637,0.00006085942,0.00004196309,0.0002346751,0.00004923495,0.00004958436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006156111,0.0008299613,0.004465057,0.00006325385,0.00006103301,0.000005556255,0.01450154,0.007140698,0.008529826,0.9384321,0.002166194,0.02374323],"study_design_scores_gemma":[0.002606701,0.002950162,0.01108352,0.0001131219,0.00002638508,0.00002002105,0.002215015,0.3437063,0.4739937,0.1571389,0.005501389,0.0006447557],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1377666,0.0001043351,0.8579801,0.00059708,0.00004481405,0.00008607958,0.000001112678,0.0000482235,0.003371658],"genre_scores_gemma":[0.8258863,0.000002316376,0.1738937,0.00006065734,0.000002472083,0.000002410328,1.090322e-7,0.000001818735,0.0001502184],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7812932,"threshold_uncertainty_score":0.217267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06679607622993636,"score_gpt":0.315854657216914,"score_spread":0.2490585809869777,"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."}}