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Record W1573265336

Shining light on black rock coatings in smelter-impacted areas

2012· article· en· W1573265336 on OpenAlexaffvenueabout
Michael Schindler, Nathalie M. Mantha, Kurt T. Kyser, Mitsuhiro Murayama, Michael F. Hochella

Bibliographic record

VenueGeoscience Canada · 2012
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsQueen's UniversityLaurentian University
Fundersnot available
KeywordsSmeltingDeposition (geology)ParticulatesAtmosphere (unit)MetalMineralogyEnvironmental chemistryMetallurgyGeologyMaterials scienceChemistrySedimentGeomorphology
DOInot available

Abstract

fetched live from OpenAlex

Earth scientists have long known of the existence of black coatings on exposed rocks in smelter-impacted areas such as Sudbury, Ontario or Rouyn-Noranda, Quebec. Black rock coatings in the Greater Sudbury area are remarkable geological records of atmospheric conditions, including mixing, scavenging, and oxidation processes, deposition rates, and the nature and source of anthropogenic releases to the atmosphere. The coatings are composed of an amorphous silica matrix that has trapped atmosphere-borne nanoparticles and has preserved their chemical and isotopic signature. These coatings are the product of high emissions of SO2 and subsequent non-stoichiometric dissolution of exposed siliceous rocks. The coatings contain spherical smelter-derived Cu–Ni-oxide particulate matter (micrometre and nanometre-sized) and metal-sulphate rich layers composed of nanometer aggregates of Fe–Cu sulphates. Lead, As, and Se-bearing nanoparticles emitted from smelters are incorporated in metal-sulphate-rich layers along the atmosphere-coating interface, presumably during coating formation. On a regional scale, ratios between different metal(loid)s in the coatings indicate that small diameter primary Pb, As and Se-bearing sulphate aerosols have been deposited at higher rates compared to larger, Ni-bearing particulate matter. High sulphur isotope values in coatings closer to smelting centres and their decrease with distance from the smelters is attributed to an increase in mixing of primary and secondary sulphates. SOMMAIRE Les geoscientifiques connaissent depuis longtemps l’existence d’une couche noire sur les roches exposees aux abords des fonderies comme celles de Sudbury en Ontario ou Rouyn-Noranda au Quebec.   Les couches noires des roches de la grande region de Sudbury constituent de remarquables enregistrements geologiques des phenomenes atmospheriques, notamment des processus de melange, de piegeage, et d'oxydation, ainsi que des taux de sedimentation et de la nature et de l’origine des rejets anthropiques dans l'atmosphere.   Ces couches noires sont constituees d'une matrice de silice amorphe qui a piege des nanoparticules atmospheriques et conserve leur signature chimique et isotopique.  Ces couches noires sont le produit de fortes emissions atmospheriques de SO2 et d’une dissolution non-stœchiometrique subsequente des roches siliceuses exposees.  Ces couches noires contiennent des spherules de particules atmospheriques d’oxydes de Cu-Ni (de taille micrometrique et nanometrique) issues de la fonderie, et des couches riches en sulfate de metaux constituees d’agregats nanometriques de sulfates de Fe-Cu.   Les nanoparticules de plomb, d’As et de Se emises par les fonderies sont incorporees dans les couches riches en sulfate de metal a l'interface de l’atmosphere et de cette couche, probablement lors de la formation de cette couche.  A l’echelle regionale, les rapports de concentration des differents metaux ou metalloides dans les couches noires indiquent que les aerosols de faible diametre de sulfate de Pb, d’As et de Se primaires ont ete deposes a des taux plus eleves que les particules nickeliferes de plus grande dimension.  Les valeurs plus elevees des isotopes du soufre observees dans les couches a proximite des fonderies et leur diminution en fonction de l’eloignement des fonderies sont attribuees a une augmentation du melange entre sulfates a l’emission et post-emission.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.208
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 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

Citations13
Published2012
Admission routes3
Has abstractyes

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