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Record W2110924022 · doi:10.2166/wqrjc.2011.124

Increasing chloride concentrations in Lake Simcoe and its tributaries

2011· article· en· W2110924022 on OpenAlexaff
Jennifer G. Winter, Amanda L. Landre, David Lembcke, Eavan M. O'Connor, Joelle D. Young

Bibliographic record

VenueWater Quality Research Journal · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsLake Simcoe Region Conservation AuthorityMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsTributaryWatershedHydrology (agriculture)Environmental scienceSalt lakeChlorideGeographyGeologyChemistryStructural basin

Abstract

fetched live from OpenAlex

Chloride concentrations in Lake Simcoe have increased significantly (P < 0.001) over a 36-year period during which the human population in the watershed has grown. Lake concentrations are now between 36 and 40 mg/L, having increased more than three-fold at the lake's outflow since 1971. Concentrations increased significantly in eight tributaries of the lake from 1993 to 2007 (P < 0.05), and were highest in those rivers draining the greatest percentage of urban land and roads, and in a river close to a major highway. The cumulative chloride load estimated at the mouths of seven rivers flowing into Lake Simcoe ranged from 11,563 to 32,107 tonnes/year from 1998 to 2007, and increased significantly over this period (P < 0.05). The fluxes or unit area loads of chloride, averaged from 2004 to 2007 for each of 10 tributaries, were positively correlated with the proportion of urban land and roads drained (P = 0.005, r = 0.80). Although Lake Simcoe is a large lake and only 12% of its watershed drains urban land and roads, evidence of road salt application can already be seen. This indicates that inputs must be reduced to preclude future ecological impacts on the lake.

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 score0.837
Threshold uncertainty score0.323

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 science0.0000.001
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 head0.147
GPT teacher head0.358
Teacher spread0.211 · 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

Citations52
Published2011
Admission routes1
Has abstractyes

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