MétaCan
Menu
← Back to cohort
Record W7024745175

Time-since-land-use-conversion differently affected soil properties in Northern Ontario's Great Clay Belt

2023· dissertation· en· W7024745175 on OpenAlexaffabout

Bibliographic record

VenueThe Atrium (University of Guelph) · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicHistorical Influence and Diplomacy
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDeforestation (computer science)ReforestationSoil carbonSoil waterLand usePopulationOrganic matterEcosystemSoil organic matterBoreal
DOInot available

Abstract

fetched live from OpenAlex

The increasing population in Ontario is straining the agricultural lands in the South. To alleviate some of this pressure, conversion of boreal forest in the Great Clay Belt of Northern Ontario has been proposed. Such conversions have the potential for deleterious impacts to soils and their ability to sequester atmospheric carbon and provide crucial ecosystem services. The purpose of this research is to assess the impact that land use conversion has on several soil properties and organic matter dynamics along a chrono sequence of up to >30-years. Results from deforestation and reforestation chrono sequences show promise for the sustainable implementation of pastoral lands and their rejuvenation should degradation occur. Interesting trends were also highlighted regarding the storage of carbon in the soil’s composite organic matter fractions. The information provided by this study highlight the potential of expanding agricultural activities to Northern Ontario while maintaining sustainability.

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 score0.025
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.240
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

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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueThe Atrium (University of Guelph)→Same topicHistorical Influence and Diplomacy→French-language works237,207→