{"id":"W3175737394","doi":"10.1109/icde51399.2021.00281","title":"Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks","year":2021,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Transformer; Artificial intelligence; Engineering; Electrical engineering; Voltage","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":[0.0004194354,0.0008264675,0.0004984036,0.0006206349,0.0002055887,0.0004627125,0.0009650086,0.0005306483,0.001654291],"category_scores_gemma":[0.001477707,0.0004268747,0.000679758,0.0007942806,0.0002300421,0.001263227,0.0005602289,0.001226468,0.0005712016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009247582,"about_ca_system_score_gemma":0.0007048179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02738085,"about_ca_topic_score_gemma":0.03339923,"domain_scores_codex":[0.9998416,0.00002791236,0.000008730053,0.00005734908,0.00003065713,0.00003375799],"domain_scores_gemma":[0.9996294,0.0001806697,0.00004393843,0.00004597011,0.00007545035,0.00002458478],"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":[0.0003444905,0.0002960021,0.006291534,0.00006703182,0.0001493992,0.0001480207,0.0000913104,0.7058749,0.005590348,0.007810372,0.006891912,0.2664446],"study_design_scores_gemma":[0.00000244718,0.000006071847,0.0001702207,0.000001093854,0.000004073352,0.000003530017,0.000002148638,0.9983038,0.0002195199,0.001197734,0.00008771392,0.000001613897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.242853,0.00154161,0.7419204,0.001009908,0.000171718,0.00008014669,0.001753837,0.003775744,0.006893659],"genre_scores_gemma":[0.9433773,0.0003663032,0.04953704,0.0002111539,0.00005804311,0.00003993181,0.002161349,0.00005991577,0.004188945],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02738085,"threshold_uncertainty_score":0.05444294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992380200671594,"score_gpt":0.1992999766944103,"score_spread":0.1793761746876944,"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."}}