The Synchrotron-based Far-infrared Spectrum of Glycolaldehyde
Bibliographic record
Abstract
Abstract Glycolaldehyde (GA) has been observed toward several different sources, with a broad range of rotational temperatures (8–300 K). At the high end, the temperature is comparable to the energy of the lowest vibrational states of GA, making the vibrational contribution to the partition function significant. Here, we report an analysis of the high-resolution far-infrared spectrum of GA, which features a plethora of well-resolved lines from 170–430 cm−1 (13–5 THz). We focus on the three fundamental vibrational bands in this range, i.e., the symmetric ν 12 bend at 282 cm−1, and the asymmetric ν 17 and ν 18 torsions at 360 and 208 cm−1, respectively. We assigned 23,266 transitions to 13,999 lines within these bands, which, when combined with the previously reported microwave and millimeter-wave spectra, allowed for refinement of the vibrationally excited rotational constants, and accurate determination of their band origins. Additionally, the assignment of a number of lines in several hot bands that are significantly populated at 300 K allowed for determination of their band origins. The rotational constants reported here should be useful in searches of vibrationally excited GA toward warm sources, and the accurately determined band origins allow for refinement of the vibrational partition function, and therefore column density, for a given excitation temperature.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".