{"id":"W2466917852","doi":"","title":"MODELING PERCEIVED USEFULNESS ON ADOPTING ON LINEBANKING THROUGH THE TAM MODEL IN A CANADIANBANKING ENVIRONMENT","year":2011,"lang":"en","type":"article","venue":"","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Latent variable; Computer science; Technology acceptance model; External variable; Variable (mathematics); The Internet; Structural equation modeling; Data science; Artificial intelligence; Usability; World Wide Web; Machine learning; Human–computer interaction; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003417687,0.0006066452,0.0004078683,0.001447175,0.001958584,0.003348663,0.001209949,0.0009716724,0.005095808],"category_scores_gemma":[0.01115695,0.0003303523,0.0007749659,0.00228547,0.001050657,0.001447725,0.00126315,0.001349794,0.0005321824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01368472,"about_ca_system_score_gemma":0.01625975,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8931245,"about_ca_topic_score_gemma":0.8990116,"domain_scores_codex":[0.9987836,0.0004392118,0.00003674172,0.000144145,0.0002202809,0.0003759796],"domain_scores_gemma":[0.9896079,0.005789184,0.000766126,0.0004292208,0.002292849,0.001114723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006221107,0.001309215,0.9198627,0.00009600689,0.0001932755,0.0003506174,0.009239883,0.02296644,0.001138602,0.007889633,0.003142922,0.03318863],"study_design_scores_gemma":[0.0001168731,0.0006789888,0.7410737,0.0001999939,0.0006071705,0.00008873381,0.02046957,0.2281401,0.0007921229,0.002121305,0.005555289,0.0001561093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952058,0.00005356064,0.000863386,0.0002192642,0.000006322374,0.00004212339,0.0002582207,0.00001343954,0.00333783],"genre_scores_gemma":[0.997059,0.00008358615,0.0009531275,0.00002854551,0.000002274737,0.00003441375,0.0002364685,0.000008351958,0.001594353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1068755,"threshold_uncertainty_score":0.2150097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.303239340944411,"score_gpt":0.3482497402822858,"score_spread":0.04501039933787476,"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."}}