{"id":"W6929207485","doi":"10.48448/s5gm-9y29","title":"Aggretriever: A Simple Approach to Aggregate Textual Representations for Robust Dense Passage Retrieval","year":2022,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Aggregate (composite); Exploit; Language model; Security token; Simple (philosophy); Code (set theory)","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":[0.001327789,0.001858013,0.001210587,0.002160963,0.0006673742,0.001659,0.003346251,0.001366322,0.01566186],"category_scores_gemma":[0.005109306,0.0006797571,0.001439558,0.001758757,0.0008990912,0.00435219,0.003507186,0.001955298,0.01158608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008828617,"about_ca_system_score_gemma":0.001544057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006878821,"about_ca_topic_score_gemma":0.01363438,"domain_scores_codex":[0.9991516,0.0001971823,0.00006836323,0.0002992132,0.0001867793,0.00009683211],"domain_scores_gemma":[0.9988548,0.0003411402,0.00007228998,0.0004536539,0.0002101067,0.00006795732],"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":[0.0004160928,0.0003612992,0.001460166,0.0005032981,0.0001604931,0.0003861368,0.0004350099,0.06138659,0.0250924,0.02200644,0.06370446,0.8240876],"study_design_scores_gemma":[0.00009696605,0.0002683858,0.0004601405,0.00004599358,0.00008550975,0.0003570318,0.0002004909,0.9030823,0.02457842,0.03390871,0.03683168,0.0000843763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.014758,0.0006765595,0.920218,0.0004290581,0.0003010397,0.0004207563,0.002721674,0.05554089,0.004934079],"genre_scores_gemma":[0.1651843,0.0004460143,0.8026069,0.0005605036,0.0001627209,0.0006062934,0.01085883,0.003443125,0.01613136],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01566186,"threshold_uncertainty_score":0.05239415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07276012225946782,"score_gpt":0.3422841557004335,"score_spread":0.2695240334409657,"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."}}