MétaCan
Menu
Back to cohort
Record W2093429038 · doi:10.1029/2007gl031474

Recent Northern Hemisphere snow cover extent trends and implications for the snow‐albedo feedback

2007· article· en· W2093429038 on OpenAlexaff
Stephen J. Déry, Ross Brown

Bibliographic record

VenueGeophysical Research Letters · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsOuranosUniversity of Northern British Columbia
Fundersnot available
KeywordsNorthern HemisphereAlbedo (alchemy)ClimatologySnowSnow lineLatitudeSnow coverSpring (device)Anomaly (physics)Environmental sciencePhysical geographyGeologyGeography

Abstract

fetched live from OpenAlex

Monotonic trend analysis of Northern Hemisphere snow cover extent (SCE) over the period 1972–2006 with the Mann‐Kendall test reveals significant declines in SCE during spring over North America and Eurasia, with lesser declines during winter and some increases in fall SCE. The weekly mean trend attains −1.28, −0.78, and −0.48 × 10 6 km 2 (35 years) −1 over the Northern Hemisphere, North America, and Eurasia, respectively. The standardized SCE time series vary and trend coherently over Eurasia and North America, with evidence of a poleward amplification of decreasing SCE trends during spring. Multiple linear regression analyses reveal a significant dependence of the retreat of the spring continental SCE on latitude and elevation. The poleward amplification is consistent with an enhanced snow‐albedo feedback over northern latitudes that acts to reinforce an initial anomaly in the cryospheric system.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.312
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), 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

Citations435
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicCryospheric studies and observationsFrench-language works237,207