{"id":"W3011701972","doi":"10.1145/3343413.3377988","title":"Update Delivery Mechanisms for Prospective Information Needs","year":2020,"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":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Automatic summarization; Computer science; Mobile device; Push technology; World Wide Web; Information retrieval; Human–computer interaction","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":["insufficient_payload"],"category_scores_codex":[0.000535014,0.00008548579,0.0001184621,0.0002092746,0.0001203184,0.0004269263,0.0003778419,0.00003418763,0.001007433],"category_scores_gemma":[0.0002788365,0.00006174896,0.00009002715,0.0006326676,0.0000143564,0.003283403,0.00009795645,0.00004367597,0.002742175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001818497,"about_ca_system_score_gemma":0.00002289622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000301438,"about_ca_topic_score_gemma":0.000001620932,"domain_scores_codex":[0.9986969,0.0000126138,0.00042411,0.00008485272,0.0006423242,0.000139147],"domain_scores_gemma":[0.9991778,0.00008245601,0.0001431858,0.0001311698,0.0003690842,0.00009632403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002304264,0.00002266835,0.001767044,0.00001360975,0.00002579861,3.77554e-7,0.008303933,0.000226346,0.0002721137,0.5938434,0.2859904,0.1093039],"study_design_scores_gemma":[0.002048099,0.0003537123,0.00665536,0.000006840602,0.00004574151,0.000001247268,0.02992327,0.08669446,0.004679262,0.0732592,0.7958558,0.0004770193],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05200046,0.000006407139,0.9183688,0.01000909,0.0002255679,0.0008451534,0.00005415289,0.0001776212,0.01831278],"genre_scores_gemma":[0.9717963,0.000004560393,0.01080434,0.01599191,0.00005138301,0.0000707698,0.00004349701,0.000004388667,0.001232845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9197958,"threshold_uncertainty_score":0.9999058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2051535071104748,"score_gpt":0.383277538045793,"score_spread":0.1781240309353183,"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."}}