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Record W4402234561 · doi:10.5194/egusphere-2024-2667

Aerosol trace element solubility and deposition fluxes over the polluted, dusty Mediterranean and Black Sea basins

2024· preprint· en· W4402234561 on OpenAlexaff
Rachel Shelley, Alex R. Baker, Max Thomas, Samuel William Murphy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAir Quality Monitoring and Forecasting
Canadian institutionsStantec (Canada)
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekNatural Environment Research CouncilSight Research UKNational Science Foundation
KeywordsAerosolTrace elementDeposition (geology)Mediterranean climateEnvironmental scienceMediterranean seaSolubilityBlack seaTRACE (psycholinguistics)OceanographyEnvironmental chemistryAtmospheric sciencesGeologyStructural basinChemistryGeochemistryGeomorphologyGeographyMeteorologyArchaeology

Abstract

fetched live from OpenAlex

Abstract. Aerosol samples collected during summer 2013 on GEOTRACES cruise GA04 in the Mediterranean and Black seas were analysed for their soluble and total metal and major ion composition. The fractional solubilities (soluble / total concentrations) of the lithogenic elements (Al, Ti, Mn, Fe, Co, Th) varied strongly with atmospheric dust loading. Solubilities of these elements in samples that contained high concentrations of mineral dust were noticeably lower than at equivalent dust concentrations over the Atlantic Ocean. This behaviour probably reflects the distinct transport and pollutant regimes of the Mediterranean basin. Elements with more intense anthropogenic sources (P, V, Ni, Cu, Zn, Cd, Pb) had a variety of largely independent sources in the region and generally displayed higher fractional solubilities than the lithogenic elements. Calculated dry deposition fluxes showed a west to east decline in the N/P ratio in deposition over the Mediterranean, a factor that contributes to the P-limited status of the eastern basin. Atmospheric deposition may make a significant contribution to the surface water budgets of Mn and Zn in the western Mediterranean.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.001
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 head0.029
GPT teacher head0.271
Teacher spread0.242 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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