Use of Airborne Gamma Radiometrics to Infer Soil Properties for a Forested Area in British Columbia, Canada
Bibliographic record
Abstract
We obtained radiometric data from a public-domain archive maintained by Natural Resources Canada and processed them to produce a ternary image for a portion of the Cariboo region. A field program was used to evaluate what information could be reliably inferred from the available data. This initial investigation confirmed that the radiometrics for this area exhibited consistent and useful patterns to interpret the lithology, mineralogy, depth, and moisture status of the surficial materials. Different colour patterns in the ternary image correlated well with different compositions of the various tills. We noted a clear association between higher values of radioactive emission and more recently deposited aeolian, alluvial, and glaciofluvial sediments that contained higher concentrations of relatively unweathered minerals. We observed a clear pattern of lower emission from wetlands and areas of wet soil. Airborne radiometrics, even at 500-m line spacing, provided invaluable and precise information—not otherwise obtainable—for mapping or modelling spatial variation in properties of the surficial material within the forested study area in British Columbia. We recommend further investigations to develop operational procedures for the use of such data in mapping surficial materials.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".