{"id":"W4408023421","doi":"10.5194/amt-18-1013-2025","title":"Product ion distributions using H <sub>3</sub> O <sup>+</sup> proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS): mechanisms, transmission effects, and instrument-to-instrument variability","year":2025,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Biological and Environmental Research; Office of Science; Alfred P. Sloan Foundation; U.S. Department of Energy","keywords":"Mass spectrometry; Chemistry; Ion; Time of flight; Proton; Analytical Chemistry (journal); Time-of-flight mass spectrometry; Product (mathematics); Physics; Nuclear physics; Chromatography; Ionization","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"],"consensus_categories":[],"category_scores_codex":[0.0005473233,0.0005401745,0.0006058106,0.00005996446,0.0001735725,0.00004079962,0.0003038579,0.0003012168,0.000008307024],"category_scores_gemma":[0.0002047076,0.0005267659,0.0001299131,0.001153758,0.00009983252,0.0002561673,0.00007571334,0.0004533704,0.000002567067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407533,"about_ca_system_score_gemma":0.00004036051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002075812,"about_ca_topic_score_gemma":6.506682e-7,"domain_scores_codex":[0.9972298,0.0001062293,0.0007086521,0.0007303924,0.000655164,0.0005697477],"domain_scores_gemma":[0.9988577,0.00006769917,0.0000775979,0.0006670999,0.0001919555,0.0001379399],"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":[0.00005176572,0.0001379583,0.000170403,0.0009519618,0.0001112707,0.000001866297,0.00002945128,0.0003408149,0.9422899,0.0005490483,0.00005415815,0.05531134],"study_design_scores_gemma":[0.0003326425,0.0002119203,0.0001879971,0.0007134014,0.0001402488,0.000005555529,0.00001959405,0.007868389,0.9825795,0.006458378,0.001038948,0.000443393],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4268703,0.0001787726,0.5683351,0.0001308927,0.00007295651,0.002554086,0.00001193578,0.001685342,0.0001606508],"genre_scores_gemma":[0.8239541,0.0002488425,0.1751602,0.00001526046,0.00002611194,0.0005226306,0.00001600681,0.00005161919,0.000005279045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3970838,"threshold_uncertainty_score":0.9997184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009156424847927336,"score_gpt":0.210857221828173,"score_spread":0.2017007969802457,"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."}}