{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01861211,0.0007313442,0.0006800396,0.002948157,0.0006731119,0.002016547,0.001069922,0.0009946532,0.0015525],"category_scores_gemma":[0.0818058,0.0003689336,0.000770266,0.001739393,0.0006953888,0.002052872,0.001886879,0.001084913,0.0007446245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008003715,"about_ca_system_score_gemma":0.001207769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027182,"about_ca_topic_score_gemma":0.001246473,"domain_scores_codex":[0.9817363,0.00830868,0.002004541,0.001019173,0.006367541,0.0005636564],"domain_scores_gemma":[0.8793364,0.06877888,0.01075783,0.005404257,0.0333781,0.002344474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001062316,0.002177948,0.6515828,0.0007955013,0.0003256164,0.0001175995,0.003680651,0.002477647,0.009582954,0.001903815,0.00249593,0.3237973],"study_design_scores_gemma":[0.0003159154,0.01093069,0.8972722,0.0005183357,0.0004113735,0.0003184038,0.004808411,0.05617059,0.01611719,0.003030372,0.009937103,0.0001694155],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8963227,0.0004529531,0.0894435,0.0002681318,0.0001011199,0.002587808,0.0009980632,0.0004561523,0.009369577],"genre_scores_gemma":[0.9396526,0.0001573538,0.05573437,0.00006995662,0.00005557072,0.002495571,0.0009862354,0.0000461082,0.0008021924],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01861211,"threshold_uncertainty_score":0.09843135,"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."}}