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Record W2047467297 · doi:10.1364/ao.40.002368

Modified Ångström exponent for the characterization of submicrometer aerosols

2001· article· en· W2047467297 on OpenAlexaff
N. T. O’Neill, Оleg Dubovik, Tom F. Eck

Bibliographic record

VenueApplied Optics · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsAngstrom exponentPhysicsExponentOpticsAngstromRADIUSEffective radiusComputational physicsWavelengthAstrophysics

Abstract

fetched live from OpenAlex

The classical Angström exponent is an operationally robust optical parameter that contains size information on all optically active aerosols in the field of view of a sunphotometer. Assuming that the optical effects of a typical (radius) size distribution can be approximated by separate submicrometer and supermicrometer components, we show that one can exploit the spectral curvature information in the measured optical depth to permit a direct estimation of a fine-mode (submicrometer) Angström exponent (alpha(f)) as well as the optical fraction of fine-mode particles (eta). Simple expressions that enable the estimation of these parameters are presented and tested by use of simulations and measurements.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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 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

Citations270
Published2001
Admission routes1
Has abstractyes

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