Bibliographic record
Abstract
The acquisition of information from the airborne gamma-ray spectra is based on the ability to evaluate photopeak areas in regular spectra from natural and other sources. In airborne gamma-ray spectrometry, extraction of photopeaks of radionuclides from regular one-second spectra is a complex problem. In the region of higher energies, difficulties are associated with low signal level, i.e. low count rates, whereas at lower energies difficulties are associated with high noises due to a high signal level. In this article, a new procedure is proposed for processing the measured spectra up to and including the extraction of evident photopeaks. The procedure consists of reducing the noise in the energy channels along the flight lines, transforming the spectra into the spectra of equal resolution, removing the background from each spectrum, sharpening the details, and transforming the spectra back to the original energy scale. The resulting spectra are better suited for examining and using the photopeaks. No assumptions are required regarding the number, locations, and magnitudes of photopeaks. The procedure does not generate negative photopeaks. The resolution of the spectrometer is used for the purpose. The proposed methodology, apparently, will contribute also to study environmental problems, soil characterization, and other near-surface geophysical methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".