AMSR-E melt patterns on the Southern Patagonia Icefield
Bibliographic record
Abstract
Abstract Passive-microwave 37 GHz vertically polarized (V) brightness temperature (Tb) measurements from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) are used to monitor the extent and timing of snowmelt on the Southern Patagonia Icefield (SPI) in Chile and Argentina. Twice daily Tb’s for 2002–08 for high-elevation (>1200 m a.s.l.) pixels exhibit a bimodal histogram, typical of snow-covered regions in Yukon, Alaskan icefields and the Greenland ice sheet. The low count between the two populations represents the Tb threshold for melt (252 K). This Tb value with the ±18 K diurnal amplitude variation threshold quantifies onset and duration of the spring melt–refreeze period and is used to identify melt regimes and seasonal Tb signals. Tb histograms for pixels west of the Andean divide have a normal distribution above the melt threshold. We interpret the Tb histogram as controlled by surface moisture; the shape and position with respect to Tb are retained with changes in both latitude and elevation, and the region is known to have a moist climate. Tb is not driven by seasonal temperature changes in the northwest sector of the icefield because the Tb threshold is exceeded 75% of the time. For all pixels, the spring melt–refreeze period has shortened by a mean of 10 days a−1 and a mean of 16 days a−1 for pixels with bimodal distributions between 2002 and 2008.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".