{"id":"W4396832761","doi":"10.1145/3613905.3651037","title":"Opportunistic Nudges for Task Migration Between Personal Devices","year":2024,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nudge theory; Computer science; Exploit; Context (archaeology); Task (project management); Database transaction; Human–computer interaction; Computer security; Database; 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":[0.003709446,0.001101287,0.0004217073,0.0006491072,0.001031894,0.001962157,0.002397336,0.001145143,0.005145498],"category_scores_gemma":[0.01149967,0.0008261923,0.0006328271,0.0003918865,0.001247133,0.004435306,0.004818251,0.00107364,0.0008227014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004437091,"about_ca_system_score_gemma":0.0007998812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008459988,"about_ca_topic_score_gemma":0.001877092,"domain_scores_codex":[0.9973449,0.001344827,0.0002323957,0.0004420966,0.0003243494,0.0003114669],"domain_scores_gemma":[0.9922901,0.003520661,0.0006540846,0.002392425,0.0004387848,0.0007041094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004509708,0.002145433,0.028085,0.003589231,0.0003941183,0.003197183,0.03133348,0.05614264,0.1504271,0.1002186,0.01838178,0.6015758],"study_design_scores_gemma":[0.001360226,0.005819977,0.03057322,0.001452201,0.0005159819,0.004852981,0.00968116,0.3084975,0.07797527,0.1143113,0.4442657,0.0006946352],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1671333,0.000609014,0.8146622,0.0005316628,0.00017742,0.001188654,0.0001496749,0.004123311,0.01142475],"genre_scores_gemma":[0.5828662,0.0002029573,0.4090923,0.000206643,0.00002596848,0.0017308,0.0001769012,0.0003532298,0.005345062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005145498,"threshold_uncertainty_score":0.01961768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4455082277136148,"score_gpt":0.4827591721399338,"score_spread":0.03725094442631904,"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."}}