{"id":"W3102013277","doi":"10.1007/jhep11%282017%29142","title":"A complete basis of helicity operators for subleading factorization","year":2017,"lang":"en","type":"article","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Nuclear Physics; Natural Sciences and Engineering Research Council of Canada; Laboratory Directed Research and Development; U.S. Department of Energy; High Energy Physics; Harvard University","keywords":"Factorization; Helicity; Physics; Quantum chromodynamics; Particle physics; Effective field theory; Formalism (music); Operator (biology); Amplitude; Operator product expansion; Mathematics; Quantum mechanics; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.0001542278,0.00009168668,0.0002154788,0.00004178648,0.0003499688,0.00006414646,0.0001701851,0.00002308988,0.00002844],"category_scores_gemma":[0.00003235439,0.00007743586,0.00007744043,0.00007418398,0.0005575382,0.0005087885,0.0001313417,0.00002512056,0.000001803484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009119082,"about_ca_system_score_gemma":0.00001855302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007150803,"about_ca_topic_score_gemma":0.000001583022,"domain_scores_codex":[0.9992232,0.000007931343,0.0003615636,0.0001054366,0.0001714414,0.000130383],"domain_scores_gemma":[0.9991683,0.00006350805,0.0003257716,0.000200813,0.0001873732,0.00005423286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008425501,0.0002357205,0.02235038,0.00005762333,0.0000690119,1.937735e-8,0.00001994249,0.00004270511,0.04020522,0.9343942,0.0003128406,0.002228116],"study_design_scores_gemma":[0.001153272,0.0002775378,0.04062837,0.00009361544,0.0000743632,2.809842e-7,0.00006141258,0.0004032132,0.9363458,0.0154799,0.005225784,0.0002564342],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9461809,0.00002026501,0.03027201,0.00008939733,0.000136099,0.0001799016,0.000503317,0.00001535863,0.02260275],"genre_scores_gemma":[0.9983997,0.000002647703,0.001134272,0.000006088289,0.00001616507,0.0000262239,0.0003934267,0.000003131028,0.00001835662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9189143,"threshold_uncertainty_score":0.3157743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069796106003177,"score_gpt":0.2624761524453927,"score_spread":0.2417781913853609,"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."}}