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Record W2806140496

The Fog Remote Sensing and Modeling (FRAM) field project and preliminary results

2006· article· en· W2806140496 on OpenAlexaffabout
Ismail Gültepe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsMeteorologyWinter stormAviationStormEnvironmental scienceTornadoGeographyClimatologyAeronauticsEngineeringGeology
DOInot available

Abstract

fetched live from OpenAlex

The main purpose of this work is to describe a major field project on fog and summarize the preliminary results. The three field phases of Fog Remote Sensing and Modeling (FRAM) project were conducted over two regions of Canada: 1) Center for Atmospheric Research Experiments (CARE), Toronto, Ontario (FRAM-C), and 2) Lunenburg, Nova Scotia (FRAM-L1;L2). The FRAM-C component representing continental fog, and FRAM-L, representing the marine fog environment, took place from November 2005 to April 2006, and during June of 2006 and 2007, respectively. The main objectives of the project were 1) better description of fog environments, 2) development of microphysical parameterizations for model applications, 3) development of remote sensing methods for fog nowcasting/forecasting, 4) understanding of issues related to instrument capabilities and improvement of the analysis, and 5) integration of model data with observations to predict and detect fog areas and particle phase. During the project phases, various measurements at the surface, including droplet spectra and concentration, aerosol concentrations, visibility, 3D turbulent wind components, radiative fluxes, precipitation

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.998

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)0.0000.000

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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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 designSimulation or modeling
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

Citations14
Published2006
Admission routes2
Has abstractyes

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