MétaCan
Menu
Back to cohort
Record W4240208157 · doi:10.26434/chemrxiv-2021-tld2h

Pre- and post-industrial levels of polycyclic aromatic hydrocarbons in sediments from the Estuary and Gulf of St. Lawrence (eastern Canada)

2021· preprint· en· W4240208157 on OpenAlexafffundabout
Anne Corminboeuf, Jean‐Carlos Montero‐Serrano, Richard St‐Louis, Allyson Dalpé, Yves Gélinas

Bibliographic record

VenueChemRxiv · 2021
Typepreprint
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsConcordia UniversityUniversité LavalUniversité du Québec à Rimouski
FundersNatural Sciences and Engineering Research Council of CanadaMarine Environmental Observation Prediction and Response NetworkUniversité du Québec à Rimouski
KeywordsEstuarySedimentBenthic zoneEnvironmental chemistryEnvironmental scienceDeposition (geology)OceanographyGeologyChemistryGeomorphology

Abstract

fetched live from OpenAlex

The concentrations of 23 polycyclic aromatic hydrocarbons (PAHs; 16 parent PAHs and 7 alkyl-PAHs) were determined in 45 surface sediment and 7 basal sediment box core samples retrieved from the Estuary and Gulf of St. Lawrence in eastern Canada. The concentration sums of 16 priority PAHs (Σ16PAHs) in the surface sediments ranged from 71 to 5672 ng g−1. Σ16PAHs in the basal sediments ranged from 93 to 172 ng g−1 among the pre-industrial samples and from 1216 to 1621 ng g−1 among the early post-industrial samples. The highest Σ16PAH values occurred in samples retrieved from the Baie-Comeau-Matane area, an area affected by intense industrial anthropogenic activities. Source-diagnostic PAH ratios suggest a predominance of pyrogenic sources via atmospheric deposition, with a minor contribution of petrogenic seabed pockmark sources. The PAH concentrations in the sediments from the study areas reveal low ecological risks to benthic or other organisms living near the water-sediment interface.

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 score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.227
Teacher spread0.206 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueChemRxivSame topicToxic Organic Pollutants ImpactFrench-language works237,207