{"id":"W4416642004","doi":"10.1103/cy84-v69x","title":"Cavity-Enhanced Doppler-Broadening Thermometry via All-Frequency Metrology","year":2025,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chinese Academy of Sciences; National Natural Science Foundation of China; Heritage Foundation of Newfoundland and Labrador","keywords":"Metrology; Doppler effect; Doppler broadening; Temperature measurement; Calibration; Measurement uncertainty","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001110389,0.0002256171,0.0004672683,0.0000497452,0.0001044525,0.00001979733,0.0004294823,0.00002948943,0.0004591155],"category_scores_gemma":[0.00008233438,0.0002018532,0.0002424377,0.0004913311,0.00009871776,0.00007616589,0.00007532527,0.0004542194,0.0002124512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083834,"about_ca_system_score_gemma":0.00002406556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004150029,"about_ca_topic_score_gemma":0.000002789694,"domain_scores_codex":[0.998679,0.00005586461,0.0002883371,0.0004396563,0.0001733998,0.0003637131],"domain_scores_gemma":[0.9988858,0.0002669015,0.0001110878,0.0006278798,0.00002822722,0.00008018131],"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":[0.000005045543,0.0001013567,0.0000988074,0.0006935864,0.0001118748,0.00000274414,0.00003022207,0.000006961789,0.9884481,0.002718231,0.004314708,0.003468326],"study_design_scores_gemma":[0.00108337,0.00004776341,0.001181086,0.002229383,0.001265365,0.00001540523,0.00002761711,0.001022672,0.8907446,0.01252807,0.08874604,0.001108649],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8005148,0.02700705,0.04779245,0.07826335,0.0002231252,0.0006803849,0.00003316058,0.0005739416,0.04491175],"genre_scores_gemma":[0.9657786,0.001459771,0.0003290521,0.03169898,0.0001972709,0.000344344,0.00004362913,0.00002119543,0.0001270944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1652639,"threshold_uncertainty_score":0.8231333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118547591386623,"score_gpt":0.3214588151911482,"score_spread":0.310273339277282,"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."}}