Neutron techniques
Bibliographic record
Abstract
The first section of this chapter briefly describes the fission and spallation mechanisms for producing neutrons. The general properties of the slow neutron spectra that they produce are discussed and the methods of using beams from steady (fission reactor) sources and pulsed (accelerator-driven) sources are compared. The second section provides an overview of the different kinds of beam-definition devices. Resolution functions are then described in the third section. Scattering lengths for neutrons are tabulated in the fourth section, and scattering and absorption cross sections, isotope effects and correction for electromagnetic interactions are discussed. The fifth section gives tables of the coefficients in analytic approximations to the form factors used in the calculation of the cross sections for magnetic scattering of neutrons. The coefficients for atoms and ions in the 3d and 4d transition series are derived from wavefunctions obtained using Hartree–Fock theory and the coefficients for the rare-earth and actinide ions are obtained by fitting the analytic forms to published form factors calculated from Dirac–Fock wavefunctions. In the final section, the absorption cross sections and 1/e penetration depths of the elements are tabulated for neutrons of 1.8 A wavelength. Keywords: absorption; choppers; collimation; cross sections; filters; magnetic form factors; mirrors; monochromators; neutron diffraction; neutron scattering; neutron-beam definition; neutrons; resolution functions; scattering lengths; spin-orientation devices; Zeeman polarizers
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.023 |
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".