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Record W2808223493 · doi:10.34194/geusb.v38.4414

Greenland, Canadian and Icelandic land-ice albedo grids (2000–2016)

2017· article· en· W2808223493 on OpenAlexaboutno aff
Jason E. Box, D. van As, Konrad Steffen

Bibliographic record

VenueGeological Survey of Denmark and Greenland Bulletin · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsAlbedo (alchemy)SnowGlacierIce-albedo feedbackEnvironmental scienceAtmospheric sciencesSunlightCryospherePhysical geographyClimatologyGeologySea iceAntarctic sea iceGeomorphologyGeographyAstronomyPhysics

Abstract

fetched live from OpenAlex

Albedo, Latin for ‘whiteness’, is a term used to describe the amount of sunlight reflected by the ground. Fresh snow albedo can exceed 85%, making it among the most reflective natural substances. Warm conditions promote snow crystal metamorphosis that, like the presence of liquid water, bring snow albedo down below 65%. With the darkening, caused by the metamorphosis, absorbed solar energy thus increases by roughly a factor of two. Seasonal snow melts over the lower reaches of a glacier leading to the exposure of bare ice with albedo below 55%. Impurities such as dust, black carbon or microbes can bring glacier-ice albedo below 30%, meaning that snow ablation gives way to impurity-rich, bare glacier ice which increases absorbed sunlight by more than a factor of three.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.219
Teacher spread0.190 · 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.

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

Citations44
Published2017
Admission routes1
Has abstractyes

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