{"id":"W1969244306","doi":"10.1002/meet.2008.1450450258","title":"Developing and evaluating a reliable measure of user engagement","year":2008,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University; Dalhousie University","funders":"Killam Trusts","keywords":"Novelty; Usability; USable; Construct (python library); Reliability (semiconductor); Exploratory factor analysis; Psychology; Measure (data warehouse); Quality (philosophy); Construct validity; Affect (linguistics); Computer science; Applied psychology; User engagement; Social psychology; Human–computer interaction; Multimedia; World Wide Web; Psychometrics; Data mining; Developmental psychology; Communication","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":[],"consensus_categories":[],"category_scores_codex":[0.001473787,0.00007477331,0.0001506538,0.00029551,0.0005291605,0.00003246342,0.0006879742,0.00004361214,1.638033e-7],"category_scores_gemma":[0.0007552031,0.00005736531,0.00003333137,0.00297276,0.002349986,0.00215281,0.0005325846,0.0001409374,2.976878e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008007697,"about_ca_system_score_gemma":0.0002113893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006299571,"about_ca_topic_score_gemma":1.26928e-7,"domain_scores_codex":[0.999009,0.000001592041,0.0002921674,0.0001492543,0.0003575278,0.0001905136],"domain_scores_gemma":[0.9968811,0.00003180261,0.0007201664,0.0001179778,0.002236154,0.00001280624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001057753,0.00001544698,0.01341166,0.0001090985,0.0000373499,1.448065e-8,0.006517553,0.00000239664,0.1652771,0.7575917,0.0008807699,0.05614636],"study_design_scores_gemma":[0.001002625,0.0009746964,0.02727305,0.0001981655,0.00002869081,0.0001558269,0.02355169,0.02180648,0.8873355,0.02609628,0.01116061,0.0004164085],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800344,0.00001180601,0.01555282,0.003713457,0.00004055005,0.0002843813,8.213377e-7,0.00007587612,0.0002859658],"genre_scores_gemma":[0.8474398,0.00003379173,0.1521611,0.0003197722,0.000002664576,0.00003399881,9.202338e-8,0.000001691892,0.000007092883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7314954,"threshold_uncertainty_score":0.8658622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04946517518963265,"score_gpt":0.3164096982166523,"score_spread":0.2669445230270197,"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."}}