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Record W6996395573

Seasonal trends in phosphorus export from three major Canadian Lake Erie tributaries

2022· dissertation· en· W6996395573 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodLiquationDiafiltrationHyporeflexiaTSG101Articular cartilage damage
DOInot available

Abstract

fetched live from OpenAlex

The re-appearance of algal blooms in Lake Erie in recent decades has been attributed to increased loading of bioavailable phosphorus (soluble reactive phosphorus; SRP) in US tributaries, a trend linked to agricultural practices, tile drainage, and climate change. Here, we explore P-loading trends for three major Canadian tributaries of the Canadian Lake Erie Basin (CLEB) and investigate if increased loading can be related to increased use of tile drainage. Our results confirm that SRP loading from the Canadian tributaries has been increasing over the past decade in the late winter early spring, and that tile drainage is a significant driver of SRP across all seasons. However, the effects of tile drainage are not consistent across all regions where climate conditions, soil characteristics and agricultural management practices vary. This study highlights the complexity of P transport via tile drains and underscores why no single solution should be applied to manage P across the CLEB.

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)0.001
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 score0.015
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.007
GPT teacher head0.180
Teacher spread0.173 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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