A new adaptive band weighting technique for hydrocarbon detection
Why this work is in the frame
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Bibliographic record
Abstract
In this study, a new approach is presented for hydrocarbon detection using hyperspectral data. The algorithm is developed based on an adaptive band weighting (ABW) technique which utilizes information in different spectral bands of the hyperspectral data to enhance the detection of desired oil signatures while suppressed the unwanted background. A constant false alarm rate (CFAR) detector is then used to obtain detected hydrocarbon under a constant false alarm rate. The algorithm has been tested using an AVIRIS hyperspectral data. A comparison study is also carried out between ABW algorithm and the Mixture Tuned Matched Filtering (MTMF) algorithm in a small sub-scene of the AVIRIS data based on the Receiver Operating Characteristic (ROC) curves from the 10 regions of interest. The presented algorithm has a higher probability of hydrocarbon detection and lower false alarm than that of MTMF results.
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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 | 0.000 |
| 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 it