{"id":"W7128938467","doi":"","title":"Neutrino Interaction Vertex Reconstruction in DUNE with Pandora Deep Learning","year":2025,"lang":"en","type":"article","venue":"Lancaster EPrints (Lancaster University)","topic":"Neutrino Physics Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National de Physique Nucléaire et de Physique des Particules; Science and Technology Facilities Council; Natural Sciences and Engineering Research Council of Canada; HORIZON EUROPE Framework Programme; Office of Science; European Commission; Ministerio de Ciencia e Innovación; Centre National de la Recherche Scientifique; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; European Regional Development Fund; U.S. Department of Energy; Junta de Andalucía; Fundação para a Ciência e a Tecnologia; Fundação de Amparo à Pesquisa do Estado de Goiás; Fermilab; UK Research and Innovation; National Science Foundation; Royal Society; Xunta de Galicia; CERN; Fundação de Amparo à Pesquisa do Estado de São Paulo; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Generalitat Valenciana","keywords":"Neutrino; Software; Vertex (graph theory); Time projection chamber; Detector; Artificial neural network; Neutrino detector; Projection (relational algebra); Deep learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006387642,0.0008587856,0.0006436178,0.0007543841,0.0005611711,0.001437277,0.002432495,0.001155786,0.008099551],"category_scores_gemma":[0.001632629,0.0006634321,0.0008239382,0.0005669584,0.0004592085,0.001521064,0.001425096,0.002036199,0.001931495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009637806,"about_ca_system_score_gemma":0.001464652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01024179,"about_ca_topic_score_gemma":0.02726202,"domain_scores_codex":[0.999791,0.00002969762,0.000008803375,0.00006144225,0.00007316286,0.00003593104],"domain_scores_gemma":[0.9997208,0.0001041384,0.00002004772,0.00005730727,0.00007288953,0.00002482736],"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":[0.0007924929,0.0004566424,0.006704564,0.0003650475,0.0004640839,0.0003952431,0.0001678947,0.394809,0.01201751,0.02847189,0.06554098,0.4898145],"study_design_scores_gemma":[0.00003080144,0.00003145589,0.0002595995,0.00001153693,0.0000104629,0.00004349171,0.00002842757,0.9841623,0.004379863,0.006407648,0.004620723,0.00001367842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07822724,0.0007955591,0.8419052,0.0006811258,0.0002449454,0.0001533677,0.00210606,0.06573611,0.01015036],"genre_scores_gemma":[0.304839,0.0002743348,0.6745027,0.0007138796,0.00004067932,0.000231322,0.007156438,0.00237642,0.009865171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01024179,"threshold_uncertainty_score":0.02709574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008396451749199943,"score_gpt":0.2314131016385957,"score_spread":0.2230166498893958,"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."}}