{"id":"W1507894344","doi":"10.1103/physrevlett.114.041802","title":"Improving Identification of Dijet Resonances at Hadron Colliders","year":2015,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Perimeter Institute","funders":"Mainz Institute for Theoretical Physics, Johannes Gutenberg University Mainz; Ontario Ministry of Research, Innovation and Science; Institut Périmètre de physique théorique; Industry Canada","keywords":"Physics; Particle physics; Large Hadron Collider; Electroweak interaction; Higgs boson; Hadron; Parton; Nuclear physics; Physics beyond the Standard Model; Standard Model (mathematical formulation); Observable; Quark; Resonance (particle physics); Vector boson; Gauge (firearms)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002893281,0.0006359585,0.0006741622,0.0028235,0.0005828883,0.00172421,0.0008493214,0.0009131064,0.001662807],"category_scores_gemma":[0.005029075,0.0004464785,0.0002909054,0.001268548,0.0003448172,0.001470125,0.001472304,0.0006418558,0.001077112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005118925,"about_ca_system_score_gemma":0.0004623765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009526836,"about_ca_topic_score_gemma":0.002219919,"domain_scores_codex":[0.9982989,0.0005959929,0.00008251567,0.0004069077,0.0004217288,0.0001938973],"domain_scores_gemma":[0.9981977,0.0007165731,0.0003725013,0.0003114506,0.0002957073,0.0001061347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001914273,0.000314918,0.1201254,0.0009705496,0.0002514488,0.001227521,0.0008350476,0.02244843,0.5729907,0.05400718,0.004044084,0.2208704],"study_design_scores_gemma":[0.0003529861,0.000763093,0.05964027,0.0001221126,0.0003444864,0.001428688,0.0004865873,0.2261462,0.6427302,0.03786616,0.02987134,0.0002480386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7807944,0.00609056,0.1864946,0.000715951,0.0002244751,0.0001061496,0.001017806,0.002758499,0.02179752],"genre_scores_gemma":[0.9265155,0.0008430255,0.07077026,0.0001646422,0.00005066993,0.00003393624,0.0002466406,0.000105907,0.001269554],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002893281,"threshold_uncertainty_score":0.01530135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02257839429228226,"score_gpt":0.3036307996286666,"score_spread":0.2810524053363844,"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."}}