{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005062174,0.0005891215,0.0004831251,0.0004534441,0.0005325576,0.0008619028,0.0007697692,0.0005529671,0.003887991],"category_scores_gemma":[0.0008381027,0.0003931565,0.0002881264,0.0005011038,0.0002449609,0.0009349906,0.000546073,0.0003264585,0.001000561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005846326,"about_ca_system_score_gemma":0.0004146919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001140678,"about_ca_topic_score_gemma":0.003331662,"domain_scores_codex":[0.9995885,0.00003976027,0.00001617726,0.00008166069,0.000195903,0.00007793507],"domain_scores_gemma":[0.9994166,0.0001736625,0.00009263564,0.0001516154,0.000141513,0.00002393768],"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":[0.0002404168,0.00006198698,0.000536761,0.0002122499,0.00001777673,0.00006223167,0.0001142131,0.0008311174,0.9822075,0.0007097537,0.000225768,0.01478017],"study_design_scores_gemma":[0.000009558978,0.000304387,0.00219422,0.000007239936,0.00001927364,0.0001169091,0.00008324248,0.003018181,0.990593,0.00007483066,0.003568581,0.00001061432],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9339167,0.005247022,0.04609084,0.0001771272,0.0001201017,0.0002055254,0.0005433388,0.0008881895,0.01281102],"genre_scores_gemma":[0.9281287,0.002627188,0.06036617,0.00007528422,0.00002186473,0.0000989517,0.0004554601,0.0003937993,0.007832518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003887991,"threshold_uncertainty_score":0.01300657,"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."}}