{"id":"W2414109967","doi":"10.1145/2901790.2901805","title":"Designing for Advanced Personalization in Personal Task Management","year":2016,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Personalization; Computer science; Task (project management); Scripting language; Human–computer interaction; Process (computing); Task management; Mechanism (biology); World Wide Web; Software engineering; Multimedia; Programming language; Systems engineering; Engineering","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":[0.01118159,0.0008398107,0.0004111136,0.0008041441,0.0008822994,0.001937634,0.001300656,0.0009408816,0.002553017],"category_scores_gemma":[0.03722734,0.0008183647,0.0005141767,0.0004312984,0.001211737,0.003106135,0.00248246,0.001291799,0.0009027167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004989863,"about_ca_system_score_gemma":0.001252157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004192512,"about_ca_topic_score_gemma":0.000604393,"domain_scores_codex":[0.9932905,0.003820566,0.0005556314,0.001182733,0.0007448676,0.0004056335],"domain_scores_gemma":[0.9632478,0.02121569,0.002907753,0.009386203,0.002061382,0.001181159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001038385,0.003133127,0.05968287,0.001293956,0.0001947164,0.0007790962,0.05112303,0.01162049,0.127633,0.01928229,0.006219641,0.7179994],"study_design_scores_gemma":[0.001188246,0.007004797,0.1543545,0.001353952,0.0007606198,0.005491879,0.01418023,0.2573848,0.2728119,0.08621059,0.1981551,0.001103274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3114468,0.0001510046,0.6744893,0.0004206357,0.00004158979,0.001340393,0.00005500759,0.005750873,0.006304426],"genre_scores_gemma":[0.612617,0.00007927041,0.3830591,0.0002364029,0.00002497063,0.0009663734,0.00007872114,0.0003995129,0.002538695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01118159,"threshold_uncertainty_score":0.0591346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2194462722949459,"score_gpt":0.4276051207220872,"score_spread":0.2081588484271413,"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."}}