{"id":"W3107952383","doi":"10.19173/irrodl.v21i4.4919","title":"Predicting Behavioural Intention of Manufacturing Engineers in Malaysia to Use E-Learning in the Workplace","year":2020,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Usability; USable; Context (archaeology); Technology acceptance model; Affect (linguistics); Psychology; Knowledge management; Applied psychology; Manufacturing; Marketing; Business; Computer science; Multimedia; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007451281,0.0002921316,0.0001529327,0.0004828005,0.0001863089,0.0007467302,0.0001407422,0.000444092,0.001530146],"category_scores_gemma":[0.003663435,0.000166053,0.0002939134,0.0003097263,0.0001469675,0.0003137992,0.0003585281,0.0004956311,0.0004455455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002054572,"about_ca_system_score_gemma":0.0004247461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003034983,"about_ca_topic_score_gemma":0.005781384,"domain_scores_codex":[0.999558,0.000137461,0.00005960248,0.00004236917,0.0001117758,0.0000907892],"domain_scores_gemma":[0.9968893,0.001126755,0.001043331,0.00009209971,0.0004059075,0.0004426034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002475175,0.0002716506,0.9895434,0.00003601011,0.00001779801,0.00004673228,0.0007395095,0.0001650648,0.0008131191,0.00002156941,0.00006164038,0.008258629],"study_design_scores_gemma":[0.000001943854,0.0002275679,0.996412,0.00002687275,0.00001398283,0.00006368235,0.00187353,0.0008084078,0.0003449715,0.00002695375,0.0001928953,0.000007234039],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992422,0.00004843368,0.0001658464,0.00003790532,0.000001878859,0.000006778832,0.00002780729,0.000002571529,0.0004665457],"genre_scores_gemma":[0.9991207,0.00009396132,0.0002474871,0.00001954744,0.000001983658,0.00000885786,0.00004642253,0.00000103351,0.0004599775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003034983,"threshold_uncertainty_score":0.006034613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2275060407451755,"score_gpt":0.4600086285432743,"score_spread":0.2325025877980988,"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."}}