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Record W7111795425

Source apportionment of visibility in Hong Kong

2010· article· en· W7111795425 on OpenAlexaboutno aff

Bibliographic record

VenueRare & Special e-Zone (The Hong Kong University of Science and Technology) · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
Fundersnot available
KeywordsVisibilitySampling (signal processing)Air pollutionPollutionData sourceApportionment
DOInot available

Abstract

fetched live from OpenAlex

A discussion covers visibility across the Victoria Harbor in Hong Kong; post study in Hong Kong, wherein the top three contributors are ammonium sulfate, elemental carbon, and organic carbon; seven pollution sources based on the characteristic explained variance values, i.e., vehicle exhaust, residual oil combustion, fresh sea salt, sea salt, secondary sulfate, secondary nitrate, and biomass burning; locations of meteorological observation stations and sampling site; data description and preprocessing; comparison of PM<sub>2.5</sub> source contributions in 00/01 and 04/05 campaigns; mass extraction efficiencies derived from MLR and PMF; and comparison of the source contribution to B<sub>ext</sub> in 00/01 and 04/05 campaign. This is an abstract of a paper presented at the 103rd Air and Waste Management Association Annual Conference and Exhibition (Calgary, Alberta, Canada 6/22-25/2010).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.166
Teacher spread0.162 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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