{"id":"W2964330731","doi":"10.21468/scipostphysproc.1.053","title":"Determining $\\alpha_s$ from hadronic $\\tau$ decay: the pitfalls of truncating the OPE","year":2019,"lang":"en","type":"article","venue":"SciPost Physics Proceedings","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Office of Science; Comisión Interministerial de Ciencia y Tecnología; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Generalitat de Catalunya; High Energy Physics; U.S. Department of Energy; Fundação de Amparo à Pesquisa do Estado de São Paulo; Centres de Recerca de Catalunya; San Francisco State University","keywords":"Algorithm; Computer science; Artificial intelligence; Machine learning; Physics","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":[0.01748593,0.003432418,0.002707025,0.003819828,0.002599171,0.003985941,0.006543362,0.001476865,0.004652146],"category_scores_gemma":[0.04646181,0.000995736,0.002393316,0.002581821,0.002734954,0.005587937,0.005059641,0.00453549,0.002192057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001566883,"about_ca_system_score_gemma":0.002623522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005558777,"about_ca_topic_score_gemma":0.005791317,"domain_scores_codex":[0.9910642,0.003835669,0.0007256424,0.0009968401,0.002652175,0.000725494],"domain_scores_gemma":[0.9790522,0.01094552,0.001581297,0.006261674,0.001702175,0.000457014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007959045,0.0003131828,0.008226966,0.001269646,0.0005866166,0.002616078,0.002103467,0.1079828,0.01816528,0.665999,0.008803821,0.1831373],"study_design_scores_gemma":[0.0001142836,0.0001154442,0.002265135,0.0004904349,0.0002034015,0.0008212307,0.0003373971,0.3650529,0.03674193,0.585305,0.008315508,0.0002373717],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08919851,0.001128315,0.8720918,0.001411469,0.0004034592,0.0002081885,0.0006379814,0.003641394,0.03127885],"genre_scores_gemma":[0.6267003,0.001940757,0.3536042,0.002090275,0.0003123384,0.0005346607,0.001339796,0.004120363,0.009357208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01748593,"threshold_uncertainty_score":0.09247553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00993413690857618,"score_gpt":0.2441551884150667,"score_spread":0.2342210515064906,"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."}}