{"id":"W4388013556","doi":"10.54097/fbem.v11i3.13186","title":"Influence of Interface Design Driven by Natural Language Processing on User Participation","year":2023,"lang":"en","type":"article","venue":"Frontiers in Business Economics and Management","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; User experience design; Human–computer interaction; User interface; User interface design; Promotion (chess); Interface (matter); Quality (philosophy); Design technology; Artificial intelligence; World Wide Web; Multimedia; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003672117,0.00005738228,0.0001080882,0.0001012897,0.00007271783,0.00006154722,0.00009528205,0.00002922925,7.513872e-7],"category_scores_gemma":[0.00007809986,0.00006154522,0.000009929181,0.0002298427,0.00009506717,0.000186846,0.00004081114,0.0000301907,0.000001944309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000600056,"about_ca_system_score_gemma":0.00001702375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001437798,"about_ca_topic_score_gemma":0.00008151436,"domain_scores_codex":[0.9994829,0.00003993643,0.000132022,0.000133341,0.0000573986,0.0001543758],"domain_scores_gemma":[0.9997993,0.00003127599,0.00006874955,0.00005196588,0.0000218494,0.00002684588],"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":[0.0002696771,0.0001961595,0.03980072,0.0004880724,0.0001001631,0.00001295835,0.04339742,0.1206797,0.00004487454,0.01227256,0.02685425,0.7558835],"study_design_scores_gemma":[0.002207909,0.00009904282,0.7240798,0.0009912926,0.00007463817,1.243173e-7,0.05509612,0.06325296,0.000262145,0.003233886,0.1496601,0.001042014],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952765,0.0001910655,0.0005271934,0.0007069045,0.0002887336,0.0002182527,0.000002603874,0.00002876999,0.002759975],"genre_scores_gemma":[0.9965033,0.001893927,0.000555577,0.00005266102,0.00001915905,0.00002427159,0.000004380933,0.000006335662,0.0009404132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7548414,"threshold_uncertainty_score":0.2509741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01091001649670563,"score_gpt":0.2640030645529491,"score_spread":0.2530930480562435,"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."}}