Bibliographic record
Abstract
All of the hyperfine interactions associated with localized and delocalized electron spin in the four isotopes of the triatomic radical H2N are treated. With nuclear Zeeman energy included, the resulting magnetic-field-dependent nuclear spin states are used to calculate the energies and nuclear spin-state mixing of the nuclear levels and the corresponding hyperfine effects upon electron paramagnetic resonance (EPR) transition energies and nuclear state transition probabilities. In the absence of nuclear spin-state mixing there would be, for example, 10 EPR transitions in D2 15N and 15 in D2 14N, all ΔmI = 0 fully allowed. In the presence of mixing, there are 243 in D2 15N and 729 in D2 14N, with large differences in probability among transitions, many 0 or small. Because of numerous (at least partially allowed) transitions, spectra from isotopes of H2 N radicals are the superposition of signals at greatly different levels of saturation. In this report, EPR spectra from D2 15N models, with either N or 2D hyperfine interaction suppressed, are simulated as a function of microwave frequency and power × spin-lattice relaxation time product. A large range of microwave frequency (and, concomitantly, magnetic field strength) will be needed to evaluate the effect of the nuclear Zeeman energy. The experimental requirements for microwave power and low temperature (long spin-lattice relaxation rate) are quantified.PACS Nos.: 33.15.Pw, 33.35.+r, 33.25.+k
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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".