A uniform flow–cavity ring-down spectrometer (UF-CRDS): A new setup for spectroscopy and kinetics at low temperature
Bibliographic record
Abstract
The UF-CRDS (Uniform Flow-Cavity Ring Down Spectrometer) is a new setup coupling for the first time a pulsed uniform (Laval) flow with a continuous wave CRDS in the near infrared for spectroscopy and kinetics at low temperature. This high resolution and sensitive absorption spectrometer opens a new window into the phenomena occurring within UFs. The approach extends the detection range to new electronic and rovibrational transitions within Laval flows and offers the possibility to probe numerous species which have not been investigated yet. This new tool has been designed to probe radicals and reaction intermediates but also to follow the chemistry of hydrocarbon chains and PAHs which play a crucial role in the evolution of astrophysical environments. For kinetics measurements, the UF-CRDS combines the CRESU technique (French acronym meaning reaction kinetics in uniform supersonic flows) with the SKaR (Simultaneous Kinetics and Ring-Down) approach where, as indicated by its name, the entire reaction is monitored during each intensity decay within the high finesse cavity. The setup and the approach are demonstrated with the study of the reaction between CN (v = 1) and propene at low temperature. The recorded data are finally consistent with a previous study of the same reaction for CN (v = 0) relying on the CRESU technique with laser induced fluorescence detection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".