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Record W2726547867 · doi:10.4236/jep.2017.86047

Trace Metal Concentrations in Pine Needles at Varying Elevation in Proximity to Roadways in an Urban Environment

2017· article· en· W2726547867 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Environmental Protection · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsMount Royal University
FundersMount Royal University
KeywordsAbies balsameaTransectEnvironmental chemistryBalsamEnvironmental scienceElevation (ballistics)BioaccumulationTrace metalPollutantBiomonitoringChemistryGeologyMetalBotanyOceanography

Abstract

fetched live from OpenAlex

Conifer needles bioaccumulate atmospheric pollutants, including trace metals, and may be used to monitor variations in atmospheric concentration. Needles were analyzed to determine whether a correlation exists between elevations and trace metal concentrations in proximity to roadways and other non-point sources. Composite samples of white spruce (Picea glauca) and balsam fir (Abies balsamea) needles were collected along hillsides in eastern and western Calgary, respectively. A combined total of 11 sites was sampled along two transects of increasing elevation. Qualitative and quantitative analysis of trace metal concentrations was completed using inductively coupled plasma-mass spectrometry (ICP-MS) and synthesized using regression analysis. The concentrations of cobalt, nickel, and calcium in the samples were found to exhibit a significant (P < 0.05) relationship with respect to elevation and proximity to roadways.

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.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.254
Teacher spread0.226 · 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