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Record W2150762837 · doi:10.1039/b200787h

Sources of lead and zinc associated with metal smelting activities in the Trail area, British Columbia, Canada

2002· article· en· W2150762837 on OpenAlexaffabout
Fariborz Goodarzi, Hamed Sanei, M Labonté, William F. A. Duncan

Bibliographic record

VenueJournal of Environmental Monitoring · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of VictoriaTeck (Canada)Geological Survey of Canada
Fundersnot available
KeywordsSmeltingEnvironmental scienceDeposition (geology)ZincZinc smeltingMossStack (abstract data type)MetallurgySlag (welding)Lead smeltingEnvironmental chemistryMining engineeringMaterials scienceGeologyChemistryEcology

Abstract

fetched live from OpenAlex

The spatial distribution and deposition of lead and zinc emitted from the Trail smelter, British Columbia, Canada, was studied by strategically locating moss bags in the area surrounding the smelter and monitoring the deposition of elements every three months. A combined diffusion/distribution model was applied to estimate the relative contribution of stack-emitted material and material emitted from the secondary sources (e.g., wind-blown dust from ore/slag storage piles, uncovered transportation/trucking of ore, and historical dust). The results indicate that secondary sources are the major contributor of lead and zinc deposited within a short distance from the smelter. Gradually, the stack emissions become the main source of Pb and Zn at greater distances from the smelter. Typical material originating from each source was characterized by SEM/EDX, which indicated a marked difference in their morphology and chemical composition.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.185
Teacher spread0.171 · 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 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

Citations32
Published2002
Admission routes2
Has abstractyes

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