ANALYSIS AND FIT OF THE FTMW SPECTRUM OF THE TWO-TOP MOLECULE N-METHYLACETAMIDE
Bibliographic record
Abstract
About 837 hyperfine components of torsion-rotation transitions in N-methylacetamide $(CH_{3}-NH-C(=O)-CH_{3})$ have been measured between 9.9 and 26.5 GHz using the jet-cooled Fourier transform microwave spectrometer at NIST. The molecule is assumed to have a plane of symmetry at equilibrium, so that a permutation-inversion group $G_{18}$ with the six symmetry classes $A_{1}, A_{2}, E_{1}, E_{2}, E_{3}, E_{4}$ is appropriate. Assignments were carried out primarily with the help of combination differences and computer-calculation guidance. A number of global least-squares fits of the transitions for all these symmetry species were carried out using a recently written two-top internal rotation program, which also includes nuclear quadrupole hyperfine interaction terms. At the time of writing the abstract, our best fit of the total data set, which involves 152 torsion-rotation levels with $J \\leq 8$ and $K \\leq 2$, required 3 hyperfine parameters and 42 torsion, rotation, and torsion-rotation parameters to obtain a root-mean-square residual of 5.7 kHz. This residual is essentially equal to the experimental measurement uncertainty because of the numerous occurrences of partially or completely blended hyperfine components. Aspects of the programming algorithm, which uses a pseudo principal-axis-method, and of the qualitative behavior of the low-barrier two-top energy levels will be discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".