Reflecting on siliceous rocks in central Australia: Using advanced remote sensing to map ancient “tool‐stone” resources
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract HyMap™ airborne hyperspectral imagery was used to discriminate and map hydrated silica mineralization in the Dalhousie Springs area of central Australia. A spectral feature fitting algorithm was used to match laboratory reference spectra with image pixel spectra, producing a scaled goodness‐of‐fit raster map of silicified “tool‐stone” sources in our study area. Subsequent fieldwork indicated that the algorithm mapped silcrete, a rock composed of hydrated silica, and incidentally, the most frequently utilized raw material for stone artifact manufacture in this area of the Australian arid zone. The soundness of our hydrated silica mineralization map is supported with field observations and spectroscopic analysis of collected silcrete samples. Independent siliceous rock mapping produced by the Commonwealth Scientific and Industry Research Organization offers additional corroboration of our results. Based on the success of our approach, we suggest that archaeologists working in Australia and in similar arid environments elsewhere have much to benefit in using advanced remote sensing products to map lithic resources, including time and cost‐saving advantages for field logistics, enriched assessments of land suitability for archaeological site types, and an improved understanding of resource distributions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it