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Record W2602440466

Organochlorine contamination of the Canadian Arctic, and speculation on future trends

2014· article· en· W2602440466 on OpenAlexaffabout
Tom Harner

Bibliographic record

VenueInternational Journal of Environment and Pollution · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnvironmental scienceArcticSnowThe arcticGlobal warmingContaminationEnvironmental protectionClimate changeEnvironmental chemistryEcologyGeographyOceanographyMeteorologyChemistryBiology
DOInot available

Abstract

fetched live from OpenAlex

Emission of organochlorine chemicals in urban, agricultural and industrial regions of the world has resulted in a substantial influx to the Canadian Arctic. Long–range atmospheric transport and what has been referred to as 'global distillation' transport many chemicals from warm source areas to cold, polar regions. Organochlorines are detected in Arctic air, water, and snow, with substantial accumulations in animals, marine mammals, and humans. This has led to concern regarding health effects to native people who consume traditional foods. Speculations on future trends of organochlorines in the Arctic is presented and related to global warming effects and the physical chemistry of the compounds of interest. It is conceivable that high levels of certain contaminants in the Arctic environment may persist for decades despite recent reductions in global emissions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.031
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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Same venueInternational Journal of Environment and PollutionSame topicToxic Organic Pollutants ImpactFrench-language works237,207