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Record W1889123826 · doi:10.1002/grl.50238

Quantifying Northern Hemisphere freshwater ice

2013· article· en· W1889123826 on OpenAlexaff
Rheannon Nancy Brooks, Terry D. Prowse, Ian Joseph O'Connell

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsEnvironment and Climate Change CanadaImpactUniversity of Victoria
Fundersnot available
KeywordsCryosphereIce sheetNorthern HemisphereClimatologySnowGlacierAntarctic sea iceSea iceArctic ice packIce-sheet modelGreenland ice sheetPhysical geographyGeologyEnvironmental scienceOceanographyGeographyGeomorphology

Abstract

fetched live from OpenAlex

The areal extent and volume of peak freshwater (river and lake) ice are quantified across the Northern Hemisphere for the period 1957–2002. Quantification is conducted using a degree‐day ice growth model and ice growth coefficients defined for 14 ice‐specific hydroclimatic regions. The model is driven by ERA‐40 gridded daily air temperature data, and the Global Lakes and Wetlands Database is employed to spatially define rivers and lakes. Results indicate that the total area covered by freshwater ice, at peak thickness, north of the January 0°C isotherm (excluding the Greenland ice sheet) is 1.7 × 10 6 km 2 and the total freshwater ice volume is 1.6 × 10 3 km 3 . This area is approximately equal to that of the Greenland ice sheet and the volume to snow on land (Northern Hemisphere). Such values now permit a more complete quantification of the cryosphere (evaluations already having been completed for other components, such as snow, glaciers, and sea ice) and provide a reference data set for assessing future climate‐related changes.

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 score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.294
Teacher spread0.223 · 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

Citations46
Published2013
Admission routes1
Has abstractyes

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