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Record W1991066381 · doi:10.3137/ao1104.2010

Derivation of an adjustment factor map for the estimation of the water equivalent of snowfall from ruler measurements in Canada

2010· article· en· W1991066381 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueATMOSPHERE-OCEAN · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsSnowWater equivalentPrecipitationRulerEnvironmental scienceGauge (firearms)MeteorologyClimatologyPhysical geographyHydrology (agriculture)GeographyGeologyArchaeologyPhysics

Abstract

fetched live from OpenAlex

Abstract This paper provides an updated fresh snowfall water equivalent adjustment factor (ρswe) map for Canada to allow the estimation of solid precipitation amount from ruler measurements of the depth of freshly fallen snow, which has been the standard method for measuring snowfall since Canadian climate measurements began in the middle of the nineteenth century. The ρswe map is created based on the comparison of corrected solid Nipher gauge precipitation to snowfall ruler depth measurements at 175 stations with more than 20 years of concurrent observations. The Nipher gauge correction process involved a careful analysis of station metadata to obtain precise information on anemometer heights and the dates that Nipher gauges were activated. The updated fresh snowfall water equivalent adjustment factor map allows estimates of ρswe to be obtained for all long‐term climate stations in Canada. The spatial pattern is consistent with processes influencing the density of fresh snowfall and its initial settling with values ranging from more than 1.5 over the Maritimes to less than 0.8 over southern‐ central British Columbia.

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.

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)0.000
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 score0.153
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.026
GPT teacher head0.231
Teacher spread0.205 · 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