{"id":"W4402615959","doi":"10.21203/rs.3.rs-4887482/v1","title":"A comparative study of target fabrication strategiesfor microgram muonic atom spectroscopy","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Particle Physics","funders":"Vlaamse regering; Engineering and Physical Sciences Research Council; KU Leuven; Fonds Wetenschappelijk Onderzoek; Suranaree University of Technology; High Energy Physics; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Microgram; Spectroscopy; Atom (system on chip); Fabrication; Physics; Exotic atom; Atomic physics; Chemistry; Materials science; Nuclear physics; Computer science; Quantum mechanics; Medicine; Parallel computing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002393135,0.0004654157,0.0009369684,0.000773781,0.00023343,0.0006871333,0.001260976,0.0003233519,0.0006483839],"category_scores_gemma":[0.00006201737,0.0004120689,0.0002010181,0.0009543224,0.0003989284,0.0001261741,0.001713895,0.002404825,0.0003095918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000703511,"about_ca_system_score_gemma":0.001276721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001525194,"about_ca_topic_score_gemma":0.0003980758,"domain_scores_codex":[0.9942081,0.001021472,0.0007418919,0.001300198,0.001629256,0.001099088],"domain_scores_gemma":[0.9969793,0.0002260894,0.000259622,0.001300981,0.001052199,0.0001818163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002201964,0.001964487,0.00048497,0.001402301,0.0001192995,0.00003174697,0.005892857,0.00005928269,0.9748448,0.006607141,0.008283572,0.00008933492],"study_design_scores_gemma":[0.000294905,0.00332542,0.0008568616,0.0005613009,0.00004378415,0.000002671905,0.006161174,0.0003401234,0.9445166,0.04236728,0.001143342,0.0003865167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861076,0.002995785,0.0006967657,0.0002150505,0.0003087184,0.004491794,0.0002064092,0.0005567055,0.004421142],"genre_scores_gemma":[0.9906606,0.0002225034,0.007182909,0.000006610872,0.0002497595,0.00111765,0.0001078036,0.00006745888,0.0003847119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03576014,"threshold_uncertainty_score":0.9998966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07090388671650841,"score_gpt":0.452578261476891,"score_spread":0.3816743747603826,"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."}}