Remote Predictive Mapping 2. Gamma-Ray Spectrometry: A Tool for Mapping Canada's North
Bibliographic record
Abstract
This paper reviews the theory, acquisition and application of gamma-ray spectrometric data for geological mapping, especially for Canada's North. Theoretical principals are reviewed and survey parameters and data acquisition procedures are discussed. Interpretation principles are then presented and various methods, utilizing computer processing, enhancement and classification procedures are introduced using many image examples. The ability of gamma-ray spectrometry to map the distribution of potassium, uranium, and thorium on the surface of the Earth provides powerful assistance for regional and local bedrock and surficial geological mapping. Important direct and indirect exploration guidance, in a wide variety of geological settings, is also provided, as is important information for environmental radiation monitoring and land-use planning. SOMMAIRE Le present article passe en revue les fondements theoriques, l'acquisition et l'application des donnees spec-trometriques du rayonnement gamma comme outil de cartographie geologique, particulierement pour le Nord canadien. On y examine les principes theoriques et on y discute des parametres de leve et des methodes d'acquisition des donnees. Puis, on y presente les principes et diverses meth-odes d'interpretation, utilisant le traitement de rehaussement et de classification par ordinateur, a partir de nombreux exemples d'images. La cartographie de la distribution du potassium, de l'uranium, et du thorium a la surface de la Terre a partir de techniques de spectrometrie du rayonnement gamma est une aide precieuse pour la cartographie geologique de surface locale et regionale. Cette technique constitue aussi un important guide d'exploration direct et indirect, dans une large gamme de contextes geologiques, tout comme une importante source d'information pour le monitorage des radiations dans l'environnement et la planification de l'amenagement du territoire.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".