{"id":"W7112773223","doi":"","title":"A Parametric Contextual Online Learning Theory of Brokerage","year":2024,"lang":"en","type":"article","venue":"Bristol Research (University of Bristol)","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche; University of Ottawa","keywords":"Regret; Asset (computer security); Parametric statistics; Context (archaeology); Online learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01185755,0.0001884395,0.0006546262,0.003510115,0.0004898502,0.0001441204,0.002281757,0.000183549,0.001505707],"category_scores_gemma":[0.01474704,0.0001923212,0.0003519402,0.007242759,0.002261621,0.0007499952,0.001099243,0.001538202,0.0005966264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003344696,"about_ca_system_score_gemma":0.0006764002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008203327,"about_ca_topic_score_gemma":0.0002754527,"domain_scores_codex":[0.9906881,0.002144346,0.0005499425,0.00093498,0.004941467,0.0007411322],"domain_scores_gemma":[0.9868652,0.009458188,0.0002226426,0.0008680662,0.002239372,0.0003464893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007345578,0.0005713305,0.001503529,0.0001943368,0.0002007796,0.001394868,0.003956992,0.001145644,0.002363975,0.006479558,0.04649139,0.934963],"study_design_scores_gemma":[0.002659504,0.002409025,0.0199089,0.0005142489,0.00006846379,0.0001391679,0.1252916,0.1537082,0.0009006315,0.04676177,0.6467624,0.000876159],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8072955,0.007891445,0.1709281,0.001117915,0.0003113197,0.0007948317,0.000368333,0.0001643952,0.01112818],"genre_scores_gemma":[0.9519945,0.0004509825,0.001677579,0.000005506156,0.00007710241,6.649215e-7,0.00002370376,0.00002711779,0.04574285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9340869,"threshold_uncertainty_score":0.9994071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2538802042348302,"score_gpt":0.4610343178363569,"score_spread":0.2071541136015267,"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."}}