{"id":"W4409287986","doi":"10.20944/preprints202504.0581.v1","title":"Barriers to AI Adoption in Supply Chain Management: Perspectives from Industry Leaders","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Supply chain; Business; Supply chain management; Industrial organization; Process management; Knowledge management; Marketing; Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006651236,0.0006152873,0.00057459,0.001291837,0.0001720056,0.0002533803,0.0016923,0.0008554494,0.005508687],"category_scores_gemma":[0.0004877151,0.0007006676,0.0001812633,0.001134796,0.0001647793,0.0008857503,0.005298068,0.002066908,0.00219949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003053734,"about_ca_system_score_gemma":0.0001319756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005901088,"about_ca_topic_score_gemma":0.0005286513,"domain_scores_codex":[0.9963106,0.00004683706,0.0006669245,0.001839736,0.0005160133,0.0006198898],"domain_scores_gemma":[0.9978225,0.00003967838,0.0002886062,0.001527096,0.0002477246,0.00007438916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000190389,0.0001616387,0.9771385,0.001029937,0.0002066381,0.0000525673,0.001780046,0.004131809,0.0001775434,0.01004199,0.002014742,0.00307418],"study_design_scores_gemma":[0.0006584458,0.000003817352,0.8913751,0.003192864,0.0002412116,6.738797e-7,0.01698913,0.001258663,0.0009610477,0.009772005,0.07410028,0.001446773],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9383541,0.0002311268,0.0008728656,0.008693821,0.002045881,0.00162141,0.0001448901,0.0003708986,0.04766494],"genre_scores_gemma":[0.9911366,0.0001474098,0.0001922764,0.003700409,0.0009638976,0.0003520262,0.000333586,0.00004844941,0.003125384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08576342,"threshold_uncertainty_score":0.9995444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1323133653163937,"score_gpt":0.3513852942028249,"score_spread":0.2190719288864312,"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."}}