Minimum relative entropy: Theory and application to surface temperature reconstruction from borehole temperature measurements
Bibliographic record
Abstract
In this paper we extend the minimum relative entropy (MRE) method to reconstruct ground surface temperature changes (GST) from borehole temperature measurements (BHT). The application of MRE to recovering GST is promising and provides an alternative to other inverse methods in geophysics. The relative entropy formulation provides the advantage of allowing for a prior bias in the estimated pdf and ‘hard’ bounds if desired. Test cases showed good recoveries of the GST. The method was utilized in recovering GST from two data sets in Canada. The Lac Dufault data gave very consistent results for different choices of a priori information and bounds. The Mariner results were not as good quality. This method has only recovered past ground surface temperatures, which does not directly provide information regarding climate change. However, results contained herein show fairly uniform temperatures until the past 100 to 500 years and in more recent times about a 4°C rise in temperature, consistent with previous published results.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".