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Record W4306680376 · doi:10.1002/ird.2763

One hundred years of drainage development in the Holland Marsh, Canada, and implications for long‐term sustainability

2022· article· en· W4306680376 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

VenueIrrigation and Drainage · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsDrainageMarshEnvironmental scienceWater qualitySustainabilityHydrology (agriculture)Water resource managementEutrophicationSwaleWetlandEnvironmental engineeringSurface runoffStormwaterEngineeringEcologyNutrient

Abstract

fetched live from OpenAlex

Abstract The low‐lying peatlands of the Holland Marsh are intensively cultivated with high‐value vegetable crops, worth some $450 million Canadian annually. This high productivity is due to the fact that there have been significant investments to empolder the marsh, through the construction of dykes, embankments, canals, ditches, tile drainage, and installation of pumping stations. However, attention must be paid to the long‐term environmental sustainability of the Holland Marsh, given the high phosphorus loads and eutrophication in Lake Simcoe, the principal drainage outlet for the agricultural run‐off from the marsh. It is important that non‐point source pollution be reduced and drainage water quality better managed. In addition to agro‐environmental best management practices, adoption of controlled drainage, and improved drainage water pumping strategies are recommended. These could help achieve the P reduction target established by the government of Ontario and the Lake Simcoe Region Conservation Authority.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.091
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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