{"id":"W1267888130","doi":"10.1609/aimag.v36i2.2581","title":"Reducing Friction for Knowledge Workers with Task Context","year":2015,"lang":"en","type":"article","venue":"AI Magazine","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Tasktop Technologies (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Knowledge worker; Task (project management); Computer science; Human–computer interaction; Context (archaeology); Knowledge management; Interface (matter); Productivity; Focus (optics); Work (physics); Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001205805,0.0001027643,0.0001495786,0.0002100246,0.0001031612,0.0002297134,0.0002675368,0.00003539738,0.0001205927],"category_scores_gemma":[0.0003328778,0.00006938322,0.00005358761,0.0005411903,0.00004008759,0.000852376,0.0000508946,0.00006550708,0.00176648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004826475,"about_ca_system_score_gemma":0.00006933138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001330615,"about_ca_topic_score_gemma":0.00008420405,"domain_scores_codex":[0.9987705,0.00003005345,0.0003178417,0.0002144201,0.0004860893,0.0001811324],"domain_scores_gemma":[0.9987499,0.0001662752,0.0001327626,0.0002608748,0.0005663562,0.0001238973],"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":[0.0001687468,0.00004469425,0.008798942,0.000004244144,0.00001281528,0.000001350966,0.002031207,0.0001643874,0.00008099541,0.001422249,0.9003733,0.086897],"study_design_scores_gemma":[0.001413562,0.0002276367,0.01413731,0.00002481858,0.00003095932,0.000004122385,0.003345123,0.006362269,0.00008742033,0.001032561,0.9731609,0.0001732945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7495753,0.0004694149,0.1193518,0.01142437,0.002081337,0.001447828,0.00004342886,0.0003083939,0.1152982],"genre_scores_gemma":[0.9544024,0.000001441675,0.001423969,0.0006316057,0.0001328557,0.00004591125,0.00001918885,0.000009307298,0.04333325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2048272,"threshold_uncertainty_score":0.9990107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2565552320589826,"score_gpt":0.4208252481487167,"score_spread":0.1642700160897341,"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."}}