{"id":"W2982964715","doi":"10.28945/4448","title":"Digital Logistics Capability: Factors Impacting Technology Acceptance","year":2019,"lang":"en","type":"article","venue":"Muma Business Review","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Technology acceptance model; Usability; Perception; Knowledge management; Business; Navy; Process management; Computer science; Psychology; Human–computer interaction","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":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007866149,0.0002679272,0.0007753195,0.0003680458,0.0001141544,0.0002071312,0.001301818,0.0002621938,0.003007655],"category_scores_gemma":[0.01090936,0.0001819826,0.0001543734,0.003543172,0.000258107,0.0006232189,0.0003512933,0.000356414,0.003240609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007701717,"about_ca_system_score_gemma":0.0000907693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006046016,"about_ca_topic_score_gemma":0.000007148891,"domain_scores_codex":[0.9973328,0.00005765626,0.0008809454,0.0006873045,0.0006512799,0.0003900174],"domain_scores_gemma":[0.9967251,0.0004296806,0.0004714588,0.001543911,0.0007501245,0.00007973496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002828544,0.00008011327,0.7457892,0.0001861365,0.00000767219,0.000006928816,0.00001393242,0.000007169846,0.00005755001,0.001155758,0.001670233,0.2510225],"study_design_scores_gemma":[0.0003402834,0.00004607051,0.5399642,0.001098724,0.00004842267,0.00008328204,0.0003847479,0.00004944784,0.00008367684,0.004357337,0.4529769,0.0005668972],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683059,0.01550587,0.003431939,0.005781539,0.0009017002,0.0007622331,0.00004667825,0.0004354963,0.004828668],"genre_scores_gemma":[0.994989,0.002199477,0.0002631784,0.0003968091,0.0000216935,0.00001528555,0.00001162344,0.00002049436,0.002082408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4513067,"threshold_uncertainty_score":0.9979037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1219595549438404,"score_gpt":0.3934124973746829,"score_spread":0.2714529424308425,"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."}}