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Record W3109829926 · doi:10.1073/pnas.1922486117

Photochemistry of oxidized Hg(I) and Hg(II) species suggests missing mercury oxidation in the troposphere

2020· article· en· W3109829926 on OpenAlexaff
Alfonso Saiz‐Lopez, Oleg Travnikov, Jeroen E. Sonke, Colin P. Thackray, Daniel J. Jacob, Javier Carmona‐García, Antonio Francés‐Monerris, Daniel Roca‐Sanjuán, A. Ulises Acuña, Juan Z. Dávalos, Carlos A. Cuevas, Martin Jiskra, Fei Wang, Johannes Bieser, J. M. C. Plane, Joseph S. Francisco

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Manitoba
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsTropospherePhotodissociationChemistryMercury (programming language)BromineAtmospheric chemistryPhotochemistryElemental mercuryEnvironmental chemistryRedoxOzoneAnalytical Chemistry (journal)Inorganic chemistryAtmospheric sciencesPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Significance The atmospheric chemistry of mercury, a global priority pollutant, is key to its transport and deposition to the surface environment. Assessments of its risks to humans and ecosystems rely on an accurate understanding of global mercury cycling. This work shows that the chemical reactions and rates currently employed to interpret Hg chemistry in the atmosphere fails to explain observed atmospheric mercury concentrations and deposition. We report that model simulations incorporating recent developments in the photoreduction mechanisms of the oxidized forms of mercury (Hg I and Hg II ) lead to a significant model underestimation of global observations of these oxidized species in the troposphere and their surface wet deposition. This implies that there must be currently unidentified mercury oxidation processes in the troposphere.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.042
GPT teacher head0.290
Teacher spread0.249 · 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

Citations99
Published2020
Admission routes1
Has abstractyes

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