{"id":"W4409748596","doi":"10.1145/3706598.3713139","title":"Canvil: Designerly Adaptation for LLM-Powered User Experiences","year":2025,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"Computer science; Adaptation (eye); Human–computer interaction; Psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000934522,0.00009239954,0.0001311594,0.0003245184,0.0002002983,0.0004305016,0.0004887303,0.00004129465,0.001193658],"category_scores_gemma":[0.000418774,0.00006488861,0.00008934525,0.0006023992,0.0000436595,0.0009297138,0.00004637262,0.00002958885,0.0001621733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002530447,"about_ca_system_score_gemma":0.00007129289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000711737,"about_ca_topic_score_gemma":0.0001893462,"domain_scores_codex":[0.9985677,0.00003373761,0.0004450735,0.000228224,0.0005526241,0.0001726291],"domain_scores_gemma":[0.9989377,0.0003893039,0.000103526,0.0002407462,0.0002817877,0.0000469454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000183767,0.0001270604,0.005434856,0.0000107815,0.00003019762,0.000001244715,0.02269049,0.000347826,0.0003387412,0.1587451,0.5494215,0.2626684],"study_design_scores_gemma":[0.001052288,0.0001517791,0.01486037,0.0000135625,0.00003040442,4.014665e-7,0.1715976,0.03584914,0.001745654,0.01199383,0.7624037,0.0003012645],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.353564,0.00005957557,0.5920835,0.001946644,0.0009376258,0.0006935771,0.000008237658,0.0001084812,0.05059833],"genre_scores_gemma":[0.899455,0.000002417729,0.008508391,0.001312764,0.00002286654,0.0002463783,0.000007963328,0.000003145187,0.09044112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5835751,"threshold_uncertainty_score":0.9997194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.367797867363472,"score_gpt":0.4785502186619129,"score_spread":0.1107523512984409,"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."}}