{"id":"W4323067312","doi":"10.48550/arxiv.2303.01103","title":"Search for Two-neutrino Double-Beta Decay of $^{136}\\rm Xe$ to the $0^+_1$ excited state of $^{136}\\rm Ba$ with the Complete EXO-200 Dataset","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Neutrino Physics Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; University of Sudbury; TRIUMF; Carleton University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Energy Research Scientific Computing Center; Deutsche Forschungsgemeinschaft; U.S. Department of Energy; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Physics; Excited state; Beta decay; Neutrino; State (computer science); Confidence interval; Sensitivity (control systems); Double beta decay; Atomic physics; BETA (programming language); Combinatorics; Particle physics; Algorithm; Statistics; Mathematics","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":[0.0006704138,0.001045053,0.0005165332,0.0005706659,0.0004533193,0.0008446895,0.0008460166,0.001011882,0.003615702],"category_scores_gemma":[0.0005560926,0.0002826338,0.0009840098,0.000490354,0.0002511037,0.000748485,0.0007921756,0.0008817049,0.001499591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000457636,"about_ca_system_score_gemma":0.0005460263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002819603,"about_ca_topic_score_gemma":0.008896008,"domain_scores_codex":[0.9996614,0.00003987908,0.00001168791,0.0001360267,0.00008507397,0.00006591523],"domain_scores_gemma":[0.9997607,0.00006440433,0.00004112716,0.00005203906,0.0000403082,0.0000415074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01001787,0.001929188,0.3109486,0.002017869,0.002688829,0.002567207,0.00021689,0.04298263,0.2461864,0.01615333,0.2620826,0.1022086],"study_design_scores_gemma":[0.001993283,0.001604003,0.2252494,0.0001844917,0.0009404703,0.003378528,0.0005684219,0.1924681,0.2439931,0.01199909,0.3173226,0.0002984344],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8874608,0.001357983,0.008087059,0.0008140904,0.000183518,0.0000973105,0.07480916,0.003511279,0.02367873],"genre_scores_gemma":[0.6887366,0.0003982941,0.01578495,0.000989055,0.00006516442,0.0001239786,0.2823625,0.0005442519,0.0109953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003615702,"threshold_uncertainty_score":0.01209575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.178454055335651,"score_gpt":0.2737090651738558,"score_spread":0.09525500983820481,"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."}}