Bibliographic record
Abstract
In this updated and significantly expanded second edition of The Mössbauer Effect, an introduction to the Mössbauer effect is provided for the non-specialist with a general background in undergraduate physics. A wide variety of Mössbauer applications are covered. These include general relativity, as well as the physical and chemical properties of materials. Applications in other fields including mineralogy, archaeology, space science, and biology are discussed. The book also contains descriptions of some more advanced Mössbauer spectroscopic techniques, such as ion implantation and synchrotron radiation based Mössbauer spectroscopy. This second edition includes a new chapter on experimental methods and updated and greatly expanded material on applications of the Mössbauer effect. Key features • Provides an introduction to the Mössbauer effect. • Aimed at non-specialists with a general background in undergraduate physics. • Provides an overview of potential applications of Mössbauer effect spectroscopy. • Gives an introduction to some modern Mössbauer spectroscopy techniques. • Offers guidance to researchers in other fields who could benefit from Mössbauer effect measurements.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.129 | 0.112 |
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".