{"id":"W6980952535","doi":"","title":"Demand Forecasting in Retail Business Using the Ensemble Machine Learning Framework - A Stacking Approach","year":2024,"lang":"en","type":"article","venue":"American Scientific Research Journal for Engineering, Technology, and Sciences (Global Society of Scientific Research and Researchers)","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bow Valley College","funders":"","keywords":"Demand forecasting; Ensemble learning; Ensemble forecasting; Multilayer perceptron; Component (thermodynamics); Artificial neural network; Sales forecasting; Perceptron","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":[0.001414347,0.0006302975,0.0008791366,0.001159155,0.0003506458,0.0008568522,0.0007528171,0.0006471046,0.0008649898],"category_scores_gemma":[0.002119345,0.0002521798,0.0007141022,0.001028397,0.0001907551,0.001486089,0.0006322595,0.0008797638,0.0002238396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005809665,"about_ca_system_score_gemma":0.0006167041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01252483,"about_ca_topic_score_gemma":0.01473921,"domain_scores_codex":[0.9995908,0.0001362731,0.00002856036,0.00008482234,0.0001000917,0.00005940026],"domain_scores_gemma":[0.999306,0.0003297223,0.00005451317,0.00005400916,0.0002162378,0.00003950739],"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":[0.0001047642,0.0001024896,0.009954787,0.00003505732,0.0001062259,0.0000755783,0.0001066179,0.8578451,0.0008945238,0.002319354,0.0008942124,0.1275613],"study_design_scores_gemma":[9.121512e-7,0.00001858041,0.000600466,0.000002556879,0.000007807987,0.000004773764,0.00001639584,0.9982461,0.0001350489,0.0008565274,0.0001075426,0.00000326149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4158566,0.001036502,0.5766956,0.0008643493,0.0001016308,0.00006200306,0.0004449955,0.0006086923,0.004329647],"genre_scores_gemma":[0.9550417,0.0004077905,0.04273232,0.00005159477,0.0000583999,0.00003044867,0.0004065382,0.00001809006,0.001253153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01252483,"threshold_uncertainty_score":0.02490389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2715901467505255,"score_gpt":0.4849824672254686,"score_spread":0.2133923204749431,"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."}}