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Record W2910167181 · doi:10.4095/221133

Characterization of smelter dust from the mineral fraction of humus collected around Rouyn-Noranda, Quebec

2005· report· en· W2910167181 on OpenAlexaffabout
R D Knight, P J Henderson

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsHumusMineralMineral dustCharacterization (materials science)SmeltingEnvironmental chemistryEnvironmental scienceChemistryMineralogyMining engineeringGeologyMetallurgySoil scienceMaterials scienceAerosolSoil water

Abstract

fetched live from OpenAlex

Microbeam analyses can be used to determine the morphology, texture, size, and abundance of smelter dust trapped in humus. Smelter dust is classified into two morphotypes and five classes on the basis of texture and element associations. Size and abundance of dusts were compiled at six sites at varied distances from the smelter. The distribution of dust reflects the geochemical signature of anthropogenic input to the humus. Notable differences in dust morphology, texture, and size suggest that part of the dust accumulation is historical and may reflect changes in smelting practice and process through time. Particles preserved in humus represent the resistant component of smelter dust. The labile dust, observed in modern emissions, is not present.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.991

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)0.0100.000

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 head0.027
GPT teacher head0.225
Teacher spread0.198 · 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 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

Citations11
Published2005
Admission routes2
Has abstractyes

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