{"id":"W2132735805","doi":"10.1016/j.physletb.2011.08.029","title":"Bi-Event Subtraction Technique at hadron colliders","year":2011,"lang":"en","type":"article","venue":"Physics Letters B","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"National Research Foundation of Korea; Ministry of Education; U.S. Department of Energy","keywords":"Physics; Particle physics; Large Hadron Collider; Event (particle physics); Decay chain; Hadron; Background subtraction; Cascade; Event reconstruction; Subtraction; Nuclear physics; Collider; Statistical physics; Mathematics","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":[0.00144339,0.001140235,0.0008083547,0.001200503,0.0008795912,0.001660184,0.002082626,0.0008222954,0.003494337],"category_scores_gemma":[0.002191493,0.0008164615,0.001061117,0.001179678,0.000591528,0.00188734,0.001847192,0.001429656,0.001413284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005445443,"about_ca_system_score_gemma":0.001014895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001435419,"about_ca_topic_score_gemma":0.001891417,"domain_scores_codex":[0.9990492,0.0002109319,0.00005268426,0.0001627706,0.0004238904,0.0001005783],"domain_scores_gemma":[0.9988123,0.0003416237,0.0001477437,0.0003392862,0.0002670931,0.00009191963],"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":[0.002645807,0.0003063861,0.01197132,0.0003958006,0.0004252251,0.001697954,0.000544454,0.1736119,0.2492497,0.1696035,0.003014865,0.3865331],"study_design_scores_gemma":[0.00006346541,0.0002084208,0.001938459,0.0000278807,0.0001209189,0.001251701,0.0000823088,0.7617783,0.1764636,0.04772345,0.01020342,0.000138095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01927102,0.0001039492,0.9776008,0.00005770001,0.00003524854,0.00002056772,0.00006933,0.0008491456,0.001992226],"genre_scores_gemma":[0.2651193,0.0002312916,0.7284218,0.0001622443,0.00003624905,0.00007165953,0.0006194513,0.0005243161,0.004813786],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003494337,"threshold_uncertainty_score":0.01168978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02106675036362686,"score_gpt":0.2472758412786729,"score_spread":0.226209090915046,"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."}}