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Record W2019974648 · doi:10.1364/ao.49.001630

Inversion of water cloud lidar signals based on accumulated depolarization ratio

2010· article· en· W2019974648 on OpenAlexaff
G. Roy, Xiaoying Cao

Bibliographic record

VenueApplied Optics · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsRoyal Military College of CanadaDefence Research and Development Canada
Fundersnot available
KeywordsLidarMolar absorptivityDepolarization ratioOpticsDepolarizationInversion (geology)ScatteringExtinction (optical mineralogy)Remote sensingMaterials scienceGeologyPhysics

Abstract

fetched live from OpenAlex

The relation between the accumulated single scattering factor and the layer accumulated depolarization ratio appears to be independent of the geometry of the measurements and contains information on the optical depth and thus on the extinction coefficient. A simple equation is developed to retrieve the extinction coefficient from the total integrated signal and the integrated depolarization ratio measurements. The results compare well with Klett and Weinman lidar inversion techniques. The results from the measurements of the integrated depolarization ratio can be used to set the far end initial extinction coefficient value required for Klett and Weinman lidar inversion or can be used directly.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.999

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)0.0020.000

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 head0.206
Teacher spread0.199 · 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.

Study designBench or experimental
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

Citations19
Published2010
Admission routes1
Has abstractyes

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