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Record W2030379029 · doi:10.1364/ol.31.001809

Simple relation between lidar multiple scattering and depolarization for water clouds

2006· article· en· W2030379029 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.

Bibliographic record

VenueOptics Letters · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsLidarMonte Carlo methodScatteringBackscatter (email)Extinction (optical mineralogy)Mie scatteringOpticsForward scatterPhysicsRemote sensingComputational physicsLight scatteringRange (aeronautics)Atmospheric opticsMaterials scienceGeologyStatisticsMathematics

Abstract

fetched live from OpenAlex

An empirical relationship is derived between the multiple-scattering fraction and the linear depolarization ratio by using Monte Carlo simulations of water clouds measured by backscatter lidar. This relationship is shown to hold for clouds having a wide range of extinction coefficients, mean droplet sizes, and droplet size distribution widths. The relationship is also shown to persist for various instrument fields of view and for measurements made within broken cloud fields. The results obtained from the Monte Carlo simulations are verified by using multiple-field-of-view lidar measurements. For space-based lidars equipped to measure linear depolarization ratios, this new relationship can be used to accurately assess signal perturbations due to multiple scattering within nonprecipitating water clouds.

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 score0.258
Threshold uncertainty score0.303

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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