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Record W2019608169 · doi:10.1002/aoc.656

Arsenic uptake by the Douglas‐fir (<i>Pseudotsuga menziesie</i>)

2004· article· en· W2019608169 on OpenAlexafffund
Corinne Haug, Kenneth J. Reimer, Walter Cullen

Bibliographic record

VenueApplied Organometallic Chemistry · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsRoyal Military College of CanadaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryArsenicArseniteArsenateDouglas firGenetic algorithmDry weightInductively coupled plasma mass spectrometryEnvironmental chemistryMass spectrometryBotanyChromatographyOrganic chemistryEcology

Abstract

fetched live from OpenAlex

Abstract The Douglas fir ( Pseudotsuga menziesie ) growing in an arsenic‐rich gold‐bearing region contains elevated arsenic concentrations in new‐growth stems (374 ppm dry weight (dw)) and needles (257 ppm dw). Speciation of methanol–water extracts by using high‐performance liquid chromatography–inductively coupled plasma mass spectrometry show that arsenite is the major species in needles but arsenate is more dominant in stems. Only traces of methylarsenicals are present. Arsenic concentrations in other tree species growing in the region are generally much lower; dimethylarsinate was extracted from a spruce cone. Copyright © 2004 John Wiley &amp; Sons, Ltd.

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 categoriesInsufficient payload (model declined to judge)
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 score0.236
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2004
Admission routes2
Has abstractyes

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