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Record W111322625 · doi:10.2166/wqrj.2007.028

Trophic Status Evaluation for 154 Lakes in Quebec, Canada: Monitoring and Recommendations

2007· article· en· W111322625 on OpenAlexaffabout
Rosa Galvez‐Cloutier, Michelle Sanchez

Bibliographic record

VenueWater Quality Research Journal · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversité Laval
FundersU.S. Environmental Protection Agency
KeywordsWatershedTrophic levelSecchi diskWater qualityEnvironmental scienceTransparency (behavior)Environmental resource managementGeographyGovernment (linguistics)Environmental monitoringEnvironmental protectionEnvironmental planningNutrientBusinessEutrophicationEcologyEnvironmental engineeringPolitical scienceComputer scienceBiology

Abstract

fetched live from OpenAlex

Abstract Based on chlorophyll a, total phosphorus, transparency (Secchi disk), and total nitrogen, 154 lakes located in southern regions of the Quebec province were classified according to their trophic status. Various classification methods were presented and discussed. The evaluation of existing relationships among quality parameters were established, and suggestions for priority actions and restoration initiatives were given. The ‘Reseau de surveillance de lacs’ of the Ministère de développement durable, environnement et parcs is considered as a very successful program that should be increasingly supported by the government. The program meets sustainable development principles in watershed management. The results showed that although the majority of lakes surveyed were within optimal conditions (oligotrophic status), 22 lakes required closer surveillance and more effective nutrient control measures.

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)0.002
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 score0.018
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.107
GPT teacher head0.409
Teacher spread0.302 · 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

Citations78
Published2007
Admission routes2
Has abstractyes

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