{"id":"W1603667236","doi":"10.48550/arxiv.1503.08541","title":"Hybrid ECAL: Optimization and Related Developments","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"Deutsches Elektronen-Synchrotron; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; CERN","keywords":"Calorimeter (particle physics); Granularity; Detector; Physics; Scintillator; Collider; Nuclear physics; International Linear Collider; Particle physics; Electronic engineering; Electrical engineering; Computer science; Engineering; Operating system","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001162144,0.001054334,0.0008463975,0.0008078023,0.0003295866,0.001633864,0.001749862,0.0007977935,0.00855103],"category_scores_gemma":[0.002723688,0.000497914,0.0007946494,0.001277122,0.0005113598,0.001447641,0.001007902,0.0009860035,0.002227938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008937241,"about_ca_system_score_gemma":0.0007802121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002575576,"about_ca_topic_score_gemma":0.002074029,"domain_scores_codex":[0.9991555,0.000196688,0.00002728261,0.0001304889,0.000386434,0.0001035928],"domain_scores_gemma":[0.998939,0.0004395276,0.00005894537,0.0002013345,0.0003143949,0.0000468078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000390863,0.0002520612,0.001239431,0.0005940435,0.0001333369,0.0001302356,0.00006248032,0.6688219,0.01062259,0.04160421,0.009029164,0.2671197],"study_design_scores_gemma":[0.00003617799,0.0001253037,0.0002598367,0.00002743437,0.00002790991,0.00006613755,0.00002765461,0.9696084,0.00589298,0.007923884,0.01598153,0.00002268739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03610314,0.00634659,0.9000183,0.0007530604,0.000198926,0.0001357764,0.0004321784,0.002991029,0.05302093],"genre_scores_gemma":[0.5066324,0.003564532,0.4691615,0.0005550426,0.0001709995,0.0002822186,0.0009474859,0.00142704,0.01725877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00855103,"threshold_uncertainty_score":0.02860606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04224015696085789,"score_gpt":0.1905525648955709,"score_spread":0.148312407934713,"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."}}