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Record W3090656336 · doi:10.1029/2004jd004929

Weather systems occurring over Fort Simpson, Northwest Territories, Canada, during three seasons of 1998–1999: 2. Precipitation features

2004· article· en· W3090656336 on OpenAlexaffabout
Ronald E. Stewart, Jason E. Burford, David Hudak, B. W. Currie, Bohdan Kochtubajda, Peter Rodriguez, Jinliang Liu

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsWave Control Systems (Canada)McMaster UniversityYork UniversityMinistry of the Environment, Conservation and ParksMcGill University
Fundersnot available
KeywordsPrecipitationSnowClimatologyRadarEnvironmental scienceSublimation (psychology)Precipitation typesAtmospheric sciencesMeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

Precipitation events were examined at Fort Simpson, Northwest Territories, Canada, during the autumn and winter of 1998 and during the spring of 1999 with a variety of observational tools, including a polarimetric radar. This location is characterized by a relatively small amount of precipitation (annual average of 450 mm), with approximately half being in the form of snow. During the observational periods, precipitation was produced within multilayered cloud systems with heights ranging up to 10 km, and instances of light snow were associated with either low (<2.5 km) or high (up to 10 km) clouds. Precipitation over the observational periods was typically produced in banded structures, was sometimes reduced because of subcloud evaporation or sublimation, and in the winter was often in the form of individual crystals. A state‐of‐the‐art weather forecasting model was often poor at simulating some of the critical features of the precipitation events, such as cloud top height and precipitation amount. In addition, it was shown that with the sensitive CloudSat radar, ∼17% of overpasses will be associated with the occurrence of detectable precipitation at Fort Simpson, but with the less sensitive Global Precipitation Measurement (GPM) radar, much of the precipitation will be undetected.

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)0.000
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 score0.089
Threshold uncertainty score0.682

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 science0.0010.000
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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

Citations17
Published2004
Admission routes2
Has abstractyes

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