{"id":"W1996204262","doi":"10.1145/2628363.2628380","title":"ProactiveTasks","year":2014,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Human–computer interaction; Variety (cybernetics); Focus (optics); Mobile device; Set (abstract data type); Context (archaeology); Multimedia; Mobile computing; Lock (firearm); Mobile interaction; World Wide Web; Artificial intelligence; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001110523,0.00003527518,0.00005572528,0.0001013728,0.00005190376,0.0001623171,0.0002705642,0.0000125025,0.002556774],"category_scores_gemma":[0.0002588124,0.00002123223,0.00003479869,0.000200539,0.00001574479,0.0004480002,0.00004583308,0.00002574369,0.004924116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004226535,"about_ca_system_score_gemma":0.000003651966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003347223,"about_ca_topic_score_gemma":0.000003382756,"domain_scores_codex":[0.9990982,0.00003028224,0.000164617,0.00009563399,0.0005361947,0.0000750774],"domain_scores_gemma":[0.9995384,0.0001148954,0.00004401401,0.0001933342,0.00007263899,0.00003674234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008257289,0.00003057245,0.03102903,7.981496e-7,0.0000044007,2.935379e-7,0.0003342694,0.00002709583,0.0001247654,0.2720462,0.1647081,0.5316862],"study_design_scores_gemma":[0.0001437092,0.00002119934,0.1545061,5.236229e-7,0.000002849925,5.594745e-7,0.000372295,0.008071194,0.0002510587,0.01423282,0.8223236,0.00007406389],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2064603,0.00000122233,0.04617958,0.001160407,0.0001177986,0.00006483803,5.309129e-7,0.00005476066,0.7459605],"genre_scores_gemma":[0.9569373,1.47881e-7,0.001178926,0.0008792534,0.00002678246,0.000003783344,8.330443e-7,0.00000128761,0.0409717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.750477,"threshold_uncertainty_score":0.998355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4263947259710769,"score_gpt":0.4778044123803234,"score_spread":0.05140968640924654,"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."}}