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Record W7132930677

Regulating and Supporting Ecosystem Services Provided by Urban Greenspace and Restored Meadows along a Hydro Corridor in Toronto

2022· dissertation· W7132930677 on OpenAlexafffundabout
Ke Qin

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsHudbay Minerals (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsSurface runoffHydrology (agriculture)EcosystemSoil conservationEcosystem servicesSoil biodiversityWetlandHabitatSoil qualityErosion
DOInot available

Abstract

fetched live from OpenAlex

The Meadoway project, led by the Toronto and Region Conservation Authority (TRCA), aims to restore 200 ha of meadow habitats along the Gatineau Hydro Corridor across Scarborough, Ontario. The hydro corridor’s transition from turf grass to deep-rooted native meadow plants is hypothesized to enhance regulating and supporting services. To evaluate this hypothesis, in-situ infiltration, penetrometer tests, and soil sampling were conducted on two pre-restored turf lands and two restored meadows in 2020. Soil samples were analyzed for bulk density, porosity, pore structure, total carbon, total nitrogen, and available phosphorus. Water balance analysis was conducted by simulating artificial rainfall events upon undisturbed vegetated soil samples accompanied by saturated hydraulic conductivity measurements. The meadow restoration altered soil structure and enhanced its runoff reduction and available water capacity, and decreased soil available phosphorus. The Meadoway can potentially enhance multiple ecosystem services including flood and erosion control, and soil quality and nutrient cycling regulation.

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 score0.106
Threshold uncertainty score0.212

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.008
GPT teacher head0.276
Teacher spread0.268 · 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 routes3
Has abstractyes

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