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Record W6981562257

Environmental and economic implications of land management changes in agricultural watersheds

2006· dissertation· en· W6981562257 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2006
Typedissertation
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsnot available
Fundersnot available
KeywordsRiparian zoneWatershedAgricultureNonpoint source pollutionTillageLand useLand managementWatershed managementAgricultural land
DOInot available

Abstract

fetched live from OpenAlex

This research developed and applied a GIS-based modelling framework that integrated a hydrologic model and a farm economic model to examine the environmental and economic implications of land management changes in terms of potential crop rotation in the Fairchild Creek watershed in southwestern Ontario. Model simulations that incorporated annual object-oriented landuse/landcover classifications revealed that both sediment loads and cropping returns are variable across space and time and that these patterns are not comparable. Furthermore, the spatial distribution of sediment load to economic output ratios are relatively stable and concentrated in areas with high sediment delivery or low crop-based economic output. These results provide practical references for watershed management agencies to understand the spatial and temporal dimensions of the tradeoffs between environmental impacts of agricultural nonpoint source pollution and economic output. Therefore, based on identifying high damage to benefit ratios, decision makers may prioritize areas to implement agricultural conservation practices such as conservation tillage and riparian buffer strips.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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
Published2006
Admission routes1
Has abstractyes

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