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Record W2073090076 · doi:10.1029/2002gl014828

Analysis of lidar measurements of ice clouds at multiple incidence angles

2002· article· en· W2073090076 on OpenAlexaboutno aff
Vincent Noël, G. Roy, Luc Bissonnette, Hélène Chepfer, Pierre Flamant

Bibliographic record

VenueGeophysical Research Letters · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
Fundersnot available
KeywordsLidarDepolarization ratioIce crystalsPolarization (electrochemistry)OpticsRemote sensingOscillation (cell signaling)Materials scienceGeologyPhysics

Abstract

fetched live from OpenAlex

The focus of this paper is the retrieval of the oscillation angle of crystals around the horizontal plane, in low‐level ice clouds, using the lidar depolarization ratio. An ice cloud located between 0.5 and 2.25 km of altitude has been studied. Measurements were taken near Montreal, on February 2nd, 2000, with a 1.06‐μm lidar with scanning capability and dual polarization. The scanning observations show high variations of both backscattering coefficient and depolarization ratio, that are usually associated with horizontally‐oriented crystals. A technique has been developed to retrieve the average crystals oscillation angle: the evolution of the measured lidar depolarization ratio with the lidar beam incidence angle on the cloud is compared with simulations of lidar depolarization ratio computed through ray‐tracing. For the fore mentioned case, the average crystal oscillation angle is estimated to be 12° and the relative quantity of oriented ice crystals in the cloud to be 20%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.061
GPT teacher head0.298
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2002
Admission routes1
Has abstractyes

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