{"id":"W4387662241","doi":"10.48550/arxiv.2310.10282","title":"Helical coil design with controlled dispersion for bunching enhancement of the TNSA protons","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Particle Accelerators and Free-Electron Lasers","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Grand Équipement National De Calcul Intensif","keywords":"Collimated light; Proton; Dispersion (optics); Laser; Electromagnetic coil; Materials science; Optics; Cutoff; Power (physics); Acceleration; Computational physics; Physics; Nuclear physics","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":[0.0001806031,0.0001848145,0.0001738459,0.0002665307,0.000260651,0.0003139883,0.0002382703,0.000233815,0.0006513837],"category_scores_gemma":[0.00026335,0.0001436655,0.0001270309,0.0002774035,0.0002962518,0.0002235395,0.0002405369,0.0001645359,0.0002648707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003244872,"about_ca_system_score_gemma":0.0002800619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002314352,"about_ca_topic_score_gemma":0.0003489789,"domain_scores_codex":[0.9999057,0.00001813352,0.000005530084,0.0000208203,0.00003156281,0.00001828219],"domain_scores_gemma":[0.9997508,0.00003959756,0.00007698599,0.00002693293,0.00007265076,0.00003303557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002450727,0.00002879111,0.0005924809,0.0000694013,0.000008805732,0.00006163315,0.00009309816,0.01127093,0.9742715,0.004062122,0.0001904557,0.009105658],"study_design_scores_gemma":[0.00006464174,0.0008251095,0.001888628,0.00001595546,0.00003590095,0.0002291959,0.00005815486,0.1255942,0.8627927,0.00145613,0.007005642,0.0000338309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8482931,0.0006869682,0.1458122,0.0001161119,0.00005755019,0.00006498786,0.00007250646,0.000395917,0.004500889],"genre_scores_gemma":[0.9711627,0.0001426723,0.02741103,0.00001508385,0.00001634172,0.0000405996,0.00003343405,0.00003394754,0.001144168],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0006513837,"threshold_uncertainty_score":0.002354324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07870155794067184,"score_gpt":0.1848322954251805,"score_spread":0.1061307374845086,"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."}}