{"id":"W4396919505","doi":"10.1088/1742-6596/2743/1/012086","title":"Optimizing Ion Optical Design for Laser Ablation Source in Mass Spectrometry","year":2024,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Laser-induced spectroscopy and plasma","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of Calgary; TRIUMF","funders":"","keywords":"Mass spectrometry; Laser ablation; Ablation; Laser; Ion; Ion source; Materials science; Chemistry; Analytical Chemistry (journal); Optics; Chromatography; Physics; Engineering; Aerospace engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0002618193,0.0001367132,0.0002228404,0.0001280524,0.00003255062,0.0001711731,0.0001069329,0.00007637123,0.00003002079],"category_scores_gemma":[0.00003107077,0.0001245753,0.00008530655,0.0002321596,0.00002510608,0.0007627758,0.000007775954,0.0003463214,0.000008454819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009765495,"about_ca_system_score_gemma":0.00009019964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.548683e-7,"about_ca_topic_score_gemma":0.000002714258,"domain_scores_codex":[0.9992273,0.00002314482,0.000289991,0.0000955997,0.0001539016,0.0002101063],"domain_scores_gemma":[0.9995619,0.0001893704,0.00004708685,0.00007219406,0.00007345434,0.00005601455],"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":[0.0001376866,0.00002949004,0.00002518059,0.0002175183,0.00009568862,0.00003781859,0.001053205,0.3463184,0.6154413,0.02313324,0.0002504532,0.01325999],"study_design_scores_gemma":[0.0002054383,0.0002143746,0.00004031065,0.000214605,0.00002827505,0.00002130326,0.0001946762,0.09235253,0.8878202,0.01827935,0.0004859207,0.0001430249],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1273524,0.0001251095,0.8711312,0.0001440152,0.0005306879,0.00009209134,0.000004571504,0.00005256389,0.0005673167],"genre_scores_gemma":[0.9380589,0.0001066493,0.06126639,0.000005928601,0.0004481287,0.000004543535,0.000002579436,0.0000256492,0.00008121321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8107066,"threshold_uncertainty_score":0.5080032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02496135559600858,"score_gpt":0.246598922475819,"score_spread":0.2216375668798105,"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."}}