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Record W2910514367 · doi:10.4095/221138

Physico-chemical characterization of airborne particulate impurities deposited in snow around a copper smelter, Rouyn-Noranda, Quebec

2005· report· en· W2910514367 on OpenAlexaffabout
Christian Zdanowicz, D A Kliza, Doğan Paktunç, Graeme Bonham-Carter

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSnowCopperParticulatesImpuritySmeltingEnvironmental chemistryCharacterization (materials science)ChemistryMetallurgyMineralogyEnvironmental scienceGeographyMaterials scienceMeteorologyNanotechnology

Abstract

fetched live from OpenAlex

Two snow surveys were conducted (1998 and 2001) in the region surrounding the copper smelter at Rouyn-Noranda, Quebec. Total loading rates of metals per year (ng/cm²/a) were determined for a large suite of elements, of which 13 (Cu, Pb, Zn, Cd, As, Sb, S, Ag, Ni, Al, Mg, Fe, Mn) are reported on here. The spatial distributions of loading rates of smelter-derived metals from both survey years show a bull's-eye pattern centred on the smelter, skewed northeast and southeast of the smelter as a consequence of the prevailing wind directions. Most element patterns can be divided into two parts, a proximal part close to the smelter with high loading rates dominated by deposition of smelter-emitted metals and a distal part in which loading rates approach an ambient background level and metals are predominantly from non-smelter sources. The radius of the area obviously affected by metal emissions is usually about 50 km. The differences in deposition rates for smelter-derived metals (Cu, Pb, Zn, As, Cd) between the two sampling years may be explained in part by changes in reported emissions between 1998 and 2001. All samples were thawed and filtered. Dissolved and particulate fractions were analyzed separately. The proportion of total metal in dissolved form provides an indication of potential bioavailability. It differs among elements, between years for the same element (due to changes in filter size), and, for some elements, with distance from the smelter.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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 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

Citations4
Published2005
Admission routes2
Has abstractyes

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