Bibliographic record
Abstract
In their historical article “Enrico Fermi in Rome, 1931–32” (Physics Today, Physics Today 0031-9228 55 6 2002 28 https://doi.org/10.1063/1.1496372. June 2002, page 28 ), authors Hans A. Bethe and Henry Bethe state, “One of Fermi’s colleagues observed the band spectrum of gaseous nitrogen and found that nitrogen nuclei obey Bose statistics.” I offer a clarification. Indeed, Franco Rasetti observed the rotational Raman spectrum of gaseous N2 in 1929. However, Walter Heitler and Gerhard Herzberg were the ones who recognized the difference in intensity alternation of rotational lines from that in H2: Even-numbered lines were more intense than the odd-numbered lines. Heitler and Herzberg therefore concluded that N nuclei obey Bose statistics. 1 1. W. Heitler, G. Herzberg, Naturwiss. 17, 673 (1929). https://doi.org/10.1007/BF01506505 The explanation was, of course, only clarified after the discovery of the neutron three years later.REFERENCESection:ChooseTop of pageREFERENCE <<1. W. Heitler, G. Herzberg, Naturwiss. 17, 673 (1929). https://doi.org/10.1007/BF01506505 , Google ScholarCrossref© 2002 American Institute of Physics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".