{"id":"W7104525402","doi":"10.54489/ijtim.v5i1.534","title":"Digital Threads and IT Power: Decoding Their Combined Effect on Manufacturing Performance","year":2025,"lang":"","type":"article","venue":"International Journal of Technology Innovation and Management (IJTIM)","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"Supply chain; Competitive advantage; Consistency (knowledge bases); Analytics; Snowball sampling; Organizational performance; Industry 4.0; Manufacturing; Supply chain management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002135463,0.0004558346,0.0003535956,0.001676914,0.0006083109,0.004246708,0.0004506389,0.0006666296,0.01041233],"category_scores_gemma":[0.01730252,0.0001545313,0.0004246481,0.002094289,0.0009986203,0.002559422,0.002942176,0.0009901295,0.00138345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007867414,"about_ca_system_score_gemma":0.0009354799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654055,"about_ca_topic_score_gemma":0.001578426,"domain_scores_codex":[0.9979815,0.0006824675,0.0001524453,0.0002357899,0.0005107435,0.0004370125],"domain_scores_gemma":[0.9798275,0.01184287,0.00373482,0.001006618,0.001215979,0.002372294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005524124,0.0006916674,0.9178756,0.0001365764,0.0001451939,0.0002144971,0.005143753,0.001220469,0.001485681,0.003488713,0.0004632966,0.06858207],"study_design_scores_gemma":[0.00001743174,0.0009437459,0.9726709,0.0001434849,0.0001235014,0.000103524,0.01321865,0.004285173,0.001431863,0.00369688,0.003333746,0.00003119849],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989247,0.0001694441,0.0009926212,0.0002589409,0.00001652844,0.00002155925,0.0001285024,0.00001523796,0.009150064],"genre_scores_gemma":[0.9989906,0.0000618347,0.0002835932,0.0000173352,0.00001057049,0.0000112889,0.0000552491,0.000005481922,0.0005640155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01041233,"threshold_uncertainty_score":0.03483272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007129379249934563,"score_gpt":0.2417797170595907,"score_spread":0.2346503378096561,"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."}}