{"id":"W2611159971","doi":"10.1145/3025453.3025982","title":"Keeping Users Engaged through Feature Updates","year":2017,"lang":"en","type":"article","venue":"","topic":"Educational Games and Gamification","field":"Psychology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Wearable computer; Activity tracker; Popularity; BitTorrent tracker; Entertainment; Computer science; Wearable technology; Human–computer interaction; Affect (linguistics); Physical activity; Multimedia; Sedentary lifestyle; User engagement; Applied psychology; Psychology; World Wide Web; Artificial intelligence; Social psychology; Physical medicine and rehabilitation; Eye tracking; Medicine","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":[0.001137052,0.0006778067,0.0005244901,0.0007447511,0.0005955804,0.001671283,0.0007851357,0.0008132639,0.003290281],"category_scores_gemma":[0.01420984,0.0003034724,0.0003933249,0.0003697153,0.0002992227,0.001391433,0.001298326,0.0007375143,0.001685439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001931944,"about_ca_system_score_gemma":0.0003331145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007929629,"about_ca_topic_score_gemma":0.001446335,"domain_scores_codex":[0.9989355,0.0002842772,0.0001142858,0.0002395074,0.0002805666,0.0001458708],"domain_scores_gemma":[0.9945034,0.002082374,0.0004588386,0.001593073,0.0009942987,0.0003680759],"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":[0.001505927,0.003075189,0.1286831,0.0007599216,0.000149395,0.0005057295,0.0164176,0.0009594507,0.07314654,0.000733148,0.004734521,0.7693294],"study_design_scores_gemma":[0.0003477226,0.006582062,0.8002963,0.0005804557,0.0009405377,0.002187404,0.01351211,0.0157399,0.07515708,0.003351674,0.08098356,0.0003212421],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776732,0.0001507354,0.01198684,0.0002140135,0.00003998145,0.0002751925,0.0001886075,0.001374596,0.008096843],"genre_scores_gemma":[0.9828814,0.0001213586,0.01079411,0.000165741,0.00003053548,0.0002593759,0.0002955529,0.0001801885,0.005271632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003290281,"threshold_uncertainty_score":0.01100713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06904645535120033,"score_gpt":0.3786939777290512,"score_spread":0.3096475223778509,"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."}}