{"id":"W4226330338","doi":"10.5267/j.ijdns.2022.4.005","title":"An empirical study of e-learning post-acceptance after the spread of COVID-19","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Technology acceptance model; Apprehension; Structural equation modeling; Psychology; Perception; E learning; Artificial neural network; Applied psychology; Usability; Empirical research; Social psychology; Coronavirus disease 2019 (COVID-19); Knowledge management; Computer science; Artificial intelligence; Educational technology; Machine learning; Mathematics education; Cognitive psychology; Medicine; Mathematics; Human–computer interaction; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001839495,0.00005852032,0.0001112611,0.0001171602,0.0002647746,0.00009469169,0.004310658,0.000007958147,0.00005087585],"category_scores_gemma":[0.000160228,0.0000403644,0.00001677626,0.0006928378,0.0002032936,0.00155868,0.00167024,0.0001794927,3.965547e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003620094,"about_ca_system_score_gemma":0.0004246672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002356868,"about_ca_topic_score_gemma":0.00001258046,"domain_scores_codex":[0.9981175,0.0001138467,0.0003495698,0.000201,0.00110279,0.000115286],"domain_scores_gemma":[0.9986302,0.0001400445,0.0003794134,0.00033416,0.0004238455,0.0000923353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003216375,0.0006031507,0.9024751,0.00000689021,0.00005955982,0.00005127671,0.008616045,0.06997035,0.0008606841,0.0009450604,0.001271421,0.01481886],"study_design_scores_gemma":[0.001349269,0.003229495,0.7663254,0.0000382659,0.00003068008,0.0009670487,0.004237199,0.2055452,0.0001959491,0.001618141,0.0161913,0.0002721323],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712831,0.000182351,0.02602668,0.001890788,0.0005160622,0.00005469915,0.00002016428,0.000005190903,0.00002097207],"genre_scores_gemma":[0.9965255,0.00004114167,0.002690086,0.0005789595,0.0001483654,0.000001259573,0.00000300495,0.000002481148,0.000009204357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1361497,"threshold_uncertainty_score":0.8010346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03221490267453801,"score_gpt":0.3449272471302651,"score_spread":0.3127123444557271,"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."}}