{"id":"W7062147032","doi":"","title":"Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network","year":2022,"lang":"en","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Large Hadron Collider; Fermi Gamma-ray Space Telescope; Work (physics); Fermilab; Energy (signal processing); National laboratory; Research center; Center (category theory)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003395446,0.0005404879,0.0003614389,0.001030989,0.0002519503,0.0008558839,0.000718244,0.0004893104,0.001607407],"category_scores_gemma":[0.0006621293,0.0003446455,0.0004990748,0.0005885572,0.0002055922,0.0007200814,0.0006899951,0.0006358023,0.0006147274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006061869,"about_ca_system_score_gemma":0.0005427286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005982876,"about_ca_topic_score_gemma":0.01078378,"domain_scores_codex":[0.9999149,0.000008183632,0.000003150483,0.00002821487,0.00002165171,0.00002385852],"domain_scores_gemma":[0.999793,0.00005239411,0.00002786133,0.00003138586,0.00006140366,0.00003398096],"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":[0.002924709,0.0003544581,0.02604517,0.000220935,0.0003619505,0.0008297474,0.0001721892,0.3592129,0.1346788,0.007290046,0.008067141,0.459842],"study_design_scores_gemma":[0.000006559942,0.00002397601,0.004289712,0.00000811979,0.00001573426,0.00004861177,0.00001254773,0.9855971,0.008080445,0.001310835,0.0005952955,0.00001098455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6989506,0.0006521614,0.2881991,0.0003341626,0.0001235261,0.00004866421,0.001739571,0.002689278,0.007262812],"genre_scores_gemma":[0.9277894,0.0002329478,0.06192677,0.00007351654,0.0000365873,0.00002177261,0.003134487,0.0002219991,0.006562546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005982876,"threshold_uncertainty_score":0.01189607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176472883865804,"score_gpt":0.2618395455698889,"score_spread":0.2400748167312308,"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."}}