{"id":"W2965290353","doi":"10.2139/ssrn.3411653","title":"Data Aggregation and Demand Prediction","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Data science; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.001414921,0.00008423184,0.00008753163,0.0001247305,0.0001481869,0.0002170134,0.0001941735,0.00003632365,0.00009926671],"category_scores_gemma":[0.00003692955,0.00007549598,0.00001966633,0.0001346822,0.00001272692,0.001522822,0.0001328947,0.0005459403,0.00007196356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005723906,"about_ca_system_score_gemma":0.0001264313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007990096,"about_ca_topic_score_gemma":0.0004330709,"domain_scores_codex":[0.9988857,0.00001016857,0.0001508623,0.0001748089,0.0001490972,0.0006293588],"domain_scores_gemma":[0.9996086,0.00001829641,0.000119641,0.0001986417,0.00004686692,0.000007948623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005549948,0.00002442676,0.661154,0.00003370697,0.00005566882,0.000001609465,0.00001827226,0.000007103195,0.0004670364,0.0195856,0.0004230084,0.3181741],"study_design_scores_gemma":[0.005306692,0.000146817,0.5229465,0.0002802512,0.0009192408,0.0008956203,0.003267175,0.04324617,0.00003451328,0.1933232,0.2285907,0.001043076],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923975,0.001511808,0.001461171,0.0003779328,0.0003988531,0.0001216287,0.000002398396,0.00004144602,0.00368726],"genre_scores_gemma":[0.9978064,0.0008211643,0.00001457432,0.0001127311,0.0005709293,8.76518e-7,0.00003503326,0.00001238818,0.0006258653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.317131,"threshold_uncertainty_score":0.3078637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476346591750275,"score_gpt":0.2302477473568043,"score_spread":0.2154842814393016,"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."}}