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Record W1984763177 · doi:10.1080/14634980903136388

Long-term trends in major ions and nutrients in Lake Ontario

2009· article· en· W1984763177 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsDreissenaWater qualityEnvironmental sciencePhosphorusWatershedNutrientHydrology (agriculture)MusselNitrateEcologyBivalviaBiologyChemistryMolluscaGeology

Abstract

fetched live from OpenAlex

The Great Lakes Surveillance Program has been monitoring water quality for almost 40 years in Lake Ontario. The program provides some of the most comprehensive, systematic and detailed information that is available in the world for such a large lake. The water quality in Lake Ontario has shown dramatic changes over the last 40 years, with the early measurements indicating high phosphorus concentrations that were subsequently reduced by management responses to the Great Lakes Water Quality Agreement. Other water quality parameters, such as some of the major ions, showed reductions during the 1970s and 1980s as well. Nitrate plus nitrite nitrogen has increased in the lake throughout the period of record, likely driven by increasing watershed and atmospheric sources. A major driver of more recent trends in water quality appears to be the invasion and subsequent expansion of invasive Dreissena mussel populations that first appeared in Lake Ontario in 1989. Total phosphorus concentrations have further declined, and the proportion of total phosphorus that is soluble is increasing, possibly due to the filtering action of these mussels. Concentrations of major ions that are incorporated in mussel shells such as calcium have declined, while those that do not, such as magnesium, have increased. Spring silica concentrations are increasing; an ominous signal of declining diatom populations, which may also be a symptom of the proliferation of invasive mussels in 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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.998

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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