MétaCan
Menu
Back to cohort
Record W2160964840 · doi:10.1139/f07-121

Response of summer chlorophyll concentration to reduced total phosphorus concentration in the Rhine River (Netherlands) and the Sacramento – San Joaquin Delta (California, USA)

2007· article· en· W2160964840 on OpenAlexvenueno aff
Erwin E. Van Nieuwenhuyse

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
FundersDepartment of Water Resources
KeywordsSan JoaquinEutrophicationPhosphorusChlorophyll aEnvironmental sciencePhotic zoneChlorophyllAnimal scienceDeltaHydrology (agriculture)NutrientEnvironmental chemistryChemistryPhytoplanktonEcologyBiologyGeologySoil science

Abstract

fetched live from OpenAlex

Reductions in wastewater loading led to significant declines in mean summer total phosphorus (TP) and chlorophyll concentration (Chl) in two large flowing water systems despite their initially shallow (<2 m) euphotic depth and continually high (>40 mg·m-3) soluble reactive P concentration. In the Rhine River, a gradual 2.7-fold reduction in TP resulted in a 4-fold decline in Chl. In the Sacramento – San Joaquin Delta, an abrupt 1.5-fold reduction in TP led to an equally abrupt 2.6-fold reduction in Chl. Neither response could be attributed to coincidental changes in flow, light, or nitrogen concentration. The slope of the response (Chl:TP) in both systems paralleled the average trajectory calculated using an among-system TP–Chl relationship for a broad cross section of flowing waters. The results suggest that TP was the principal determinant of Chl in both systems and that control of phosphorus loading may be an effective tool for managing eutrophication in other flowing water systems with relatively high (10–100 mg·m-3) soluble reactive P concentrations.

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 score0.160
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations35
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicSoil and Water Nutrient DynamicsFrench-language works237,207