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Record W1988258784 · doi:10.1029/2009eo160003

Mineral Dust and Climate: Working Group on Dust and Climate Joint INQUA/QUEST Workshop; Villefranche‐sur‐Mer, France, 19–22 October 2008

2009· article· en· W1988258784 on OpenAlexfundno aff
Barbara A. Maher, Sandy P. Harrison

Bibliographic record

VenueEos · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
FundersNational Space OrganizationSimon Fraser University
KeywordsMineral dustBiogeochemical cycleRadiative forcingEnvironmental scienceIron fertilizationEarth scienceClimate changeDeposition (geology)AerosolAtmospheric sciencesAtmospheric dustClimatologyOceanographyGeologyMeteorologyEnvironmental chemistryChemistryGeographyStructural basinGeomorphology

Abstract

fetched live from OpenAlex

Mineral aerosol (referred to here as “dust”) is an active climate and paleoclimate system component that may significantly influence the radiative properties of the atmosphere, as well as ocean and atmospheric carbon dioxide (CO 2 ) concentrations, through processes such as iron fertilization. The integrative, cross‐cutting examination of the role and significance of dust provides the rationale for the Dust Indicators and Records of Terrestrial and Marine Paleoenvironments (DIRTMAP) working group sponsored by the International Union of Quaternary Research and the Natural Environment Research Council's Quantifying and Understanding the Earth System (QUEST) program. The working group aims to initiate coordinated progress to improve the representation of dust properties in dust cycle models, with particular focus on dust mineralogy, such as the concentrations of iron oxides and oxyhydroxides as either nanoparticles or mineral coatings, and particle size distribution. These two sets of factors are potentially significant in assessing the effects of dust on both radiative forcing and biogeochemical cycling. The working group also aims to improve model simulation of dust source regions, the episodic nature of dust emissions, and amounts of dust deposition over the continents.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

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)0.0010.000

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 head0.014
GPT teacher head0.217
Teacher spread0.203 · 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
Published2009
Admission routes1
Has abstractyes

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