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Record W2023092830 · doi:10.1029/2006gl026704

Accelerated melting of Himalayan snow and ice triggers pronounced changes in a valley peatland from northern India

2006· article· en· W2023092830 on OpenAlexaff
Kathleen M. Rühland, N. R. Phadtare, S. J. Sangode, John P. Smol

Bibliographic record

VenueGeophysical Research Letters · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsPeatSnowMonsoonPhysical geographyGlacial periodSnow linePlateau (mathematics)PermafrostPrecipitationSnowmeltClimate changeEnvironmental scienceSurface runoffGeologyClimatologyEcologyGeographyOceanographyGeomorphology

Abstract

fetched live from OpenAlex

The Himalayan region of northern India depends on monsoon rains, together with snow and glacial melt, to supply life‐sustaining water to one of the world's most densely populated areas. Here we provide high‐resolution pollen and diatom evidence from a peat deposit in the Pinder Valley that shows a synchronous and abrupt ecosystem turnover toward a wetter state in the last two centuries that exceeded changes recorded over the last three millennia. Contrary to expectations, there was no relationship between recent proxy changes and summer monsoon precipitation. Strong relationships, however, were found with winter climate data. We link this recent unprecedented wetness to marked warming at higher elevations resulting in increased seasonal runoff and associated climatic feedbacks in this snow and ice‐melt dominated region. In contrast to the expected desiccation and decomposition of most peat systems with warming, this site has instead become the wettest in its ca. 3500‐year history.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.278
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations112
Published2006
Admission routes1
Has abstractyes

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