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Record W2463965204 · doi:10.1080/14634988.2016.1172906

Trends in Hamilton Harbour suspended sediment quality

2016· article· en· W2463965204 on OpenAlexaff
Debbie Burniston, Julia Jia, Murray N. Charlton, Lina Thiessen, Brian E. McCarry, Chris Marvin

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsMcMaster UniversityEnvironment and Climate Change Canada
FundersScience and Technology Directorate
KeywordsHarbourSedimentEnvironmental scienceWatershedShoreWater qualityContaminationHydrology (agriculture)OceanographyEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Suspended sediment quality in Hamilton Harbour has been assessed as part of a long-term monitoring study (1987–2012). Sampling locations reflected a range of shoreline activities and sources of chemical contamination to the harbour. Temporal data showed a trend toward decreasing levels of contamination by polycyclic aromatic hydrocarbons and polychlorinated biphenyls over the period from the late 1980s to the early 1990s, with a subsequent leveling off over the next two decades. The highest concentrations of both contaminants were detected in areas impacted by industrial activities along the southern shoreline and Windermere Arm, and deep-water areas of the harbour where fine-grained sediments ultimately accumulate. Areas of the harbor discharging residential or rural parts of the watershed exhibited generally lower levels of contamination. In addition to the relatively higher contaminant levels, areas along the southern shoreline and Windermere Arm characterized by historical industrial activities and associated contaminated sediments exhibited chemical profiles indicating an impact on suspended sediment and bottom sediment quality throughout the harbour. Continued monitoring after scheduled remedial activities should provide an assessment of the overall efficacy of management actions to improve sediment quality in Hamilton Harbour.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.025
GPT teacher head0.304
Teacher spread0.279 · 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 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

Citations13
Published2016
Admission routes1
Has abstractyes

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