{"id":"W4284887612","doi":"10.1287/opre.2022.2301","title":"Data Aggregation and Demand Prediction","year":2022,"lang":"en","type":"article","venue":"Operations Research","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Aggregate (composite); Cluster analysis; Data aggregator; Benchmark (surveying); Data set; Data mining; Stock (firearms); Flexibility (engineering); Econometrics; Artificial intelligence; Statistics; Economics; Mathematics","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":[0.005358241,0.001277183,0.001275494,0.002572886,0.0009007166,0.002769008,0.001133157,0.001106468,0.001455558],"category_scores_gemma":[0.02491436,0.0006570309,0.0009115569,0.005110089,0.0006782984,0.003206748,0.002004723,0.002011647,0.0007851921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00113145,"about_ca_system_score_gemma":0.001372564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007611865,"about_ca_topic_score_gemma":0.004926097,"domain_scores_codex":[0.9945412,0.002073431,0.0004890853,0.001096049,0.001532021,0.0002682279],"domain_scores_gemma":[0.9847645,0.008050845,0.001103724,0.003403903,0.002460153,0.0002168517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004347492,0.0002994061,0.03898171,0.0005619904,0.0004601929,0.0003367254,0.0005644286,0.4377213,0.004498758,0.04182368,0.02269896,0.4516181],"study_design_scores_gemma":[0.00003296231,0.0001122534,0.0071256,0.0001112322,0.00008848809,0.0001661329,0.0002779712,0.9001901,0.004914734,0.06947814,0.01743306,0.00006927278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06620613,0.003371398,0.9094673,0.003777992,0.0005803924,0.0002751326,0.002866722,0.001937054,0.01151785],"genre_scores_gemma":[0.7382302,0.002045238,0.2523126,0.0006035352,0.0005140539,0.0002952108,0.004033891,0.0001393174,0.001825973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007611865,"threshold_uncertainty_score":0.02833736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6061308537931067,"score_gpt":0.5596009659608996,"score_spread":0.04652988783220713,"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."}}