{"id":"W7095801584","doi":"","title":"Canadian Imperial Bank of Commerce Global Analytics","year":2013,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytics; E-commerce; The Internet; Government (linguistics); Big data","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001944192,0.001754396,0.0009984937,0.01082935,0.005903889,0.0181566,0.001620623,0.002022908,0.2020705],"category_scores_gemma":[0.01124947,0.0009545729,0.000812772,0.01887875,0.001615878,0.00558665,0.002151293,0.002756238,0.07280446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02759176,"about_ca_system_score_gemma":0.05619841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8039479,"about_ca_topic_score_gemma":0.8127376,"domain_scores_codex":[0.9949585,0.0001947419,0.0002198575,0.0005692954,0.003531724,0.0005259626],"domain_scores_gemma":[0.9876443,0.0006537988,0.0003463294,0.0008744115,0.009513542,0.0009675185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002952525,0.00001051143,0.0009936257,0.00009742418,0.000009803442,0.00005286173,0.00006549428,0.0001336007,0.00007325691,0.01725738,0.9276375,0.05363917],"study_design_scores_gemma":[0.000006417444,0.00000451502,0.002091938,0.00009845647,0.000009952792,0.00003820477,0.0001607961,0.0003602886,0.0001190213,0.001295557,0.9957926,0.00002209762],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002690532,0.005936639,0.001667057,0.03259906,0.002622121,0.0001562429,0.05129657,0.002208056,0.9008237],"genre_scores_gemma":[0.02497908,0.01264903,0.006163789,0.003130941,0.0005475925,0.0001166183,0.04361279,0.001135933,0.9076642],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8039479,"threshold_uncertainty_score":0.6759931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170713889851647,"score_gpt":0.2150923799879997,"score_spread":0.2033852410894833,"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."}}