{"id":"W4409603855","doi":"10.61091/jcmcc127b-176","title":"Research on AIGC-based Supply Chain Inventory Demand Forecasting Model and Nonlinear Optimization Strategy","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Demand forecasting; Nonlinear system; Operations research; Computer science; Economics; Business; Engineering; Marketing; Physics","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":[0.0004826928,0.0006347839,0.0006126551,0.0005407507,0.0004348056,0.001091739,0.001136578,0.0008013399,0.001492733],"category_scores_gemma":[0.0007600333,0.0003378452,0.0006079171,0.0009490371,0.000402132,0.001276321,0.0005966029,0.0009115592,0.0002414903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187296,"about_ca_system_score_gemma":0.001556725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04933729,"about_ca_topic_score_gemma":0.01752572,"domain_scores_codex":[0.999775,0.00004138223,0.00001334794,0.00006298265,0.00007330402,0.00003403717],"domain_scores_gemma":[0.9997988,0.00006820896,0.00002439322,0.00001156817,0.00008169439,0.00001531912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001732192,0.00001888018,0.000817201,0.00003769679,0.00002127143,0.00003397184,0.00003512277,0.9737754,0.0005580725,0.005086887,0.0006064597,0.01899174],"study_design_scores_gemma":[0.00000123657,0.000004140668,0.00006456472,0.000001627152,0.000002871838,0.000003562036,0.000003767027,0.9991431,0.0000642024,0.0005794077,0.0001297845,0.000001679531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07040144,0.001225122,0.9119634,0.0007972287,0.0001123351,0.00006503103,0.0001595315,0.0004532295,0.01482268],"genre_scores_gemma":[0.9476696,0.0008905693,0.04369854,0.0001409709,0.00005251606,0.0001031059,0.0002855278,0.00004098842,0.007118232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04933729,"threshold_uncertainty_score":0.09810024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03555767876782275,"score_gpt":0.2920571430530928,"score_spread":0.2564994642852701,"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."}}