Assessment of Acid Sulphate Soil both on surface and in subsurface using hyperspectral data
Bibliographic record
Abstract
Acid sulphate soils (ASS) are widely spread around the world and are potentially harmful to the environment due to their strong acidity producing ability and their capability to release trace metals. Secondary iron-bearing minerals produced by ASS, have diagnostic spectral features in the visible-near infrared to short-wave infrared spectral range and can be good indicators to the severity of the effects of ASS. Therefore, it is possible to detect ASS using hyperspectral sensing by mapping these indicative iron-bearing minerals. Iron oxides, hydroxides, hydroxysulphates, as well as noniron-bearing minerals, were mapped using airborne Hyperspectral Mapper data. Subsequently, a soil pH map of the surface was deduced according to the relationship between the indicative mineral species and measured pH values. Furthermore, this study investigated the presence of ASS in the subsurface by the proximal hyperspectral sensing HyLogger system, together with soil coring and soil property measurements. This allowed the acquisition of mineralogy, pH, and other soil properties at different subsurface depths. Thus, comprehensive understanding and estimation of ASS, both on the surface and in the subsurface, were attained.
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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 | 0.001 | 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".