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Record W6992591068

Mapping and monitoring soil organic carbon in the Clay Belt of Northern Ontario

2021· dissertation· en· W6992591068 on OpenAlexfundaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsnot available
FundersMinistry of Agriculture, Food and Rural AffairsMitacsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsSoil carbonTotal organic carbonNatural (archaeology)Sampling (signal processing)PopulationDisturbance (geology)Digital soil mappingSoil classificationLand use
DOInot available

Abstract

fetched live from OpenAlex

The increasing population is demanding more food, fuel, fiber and energy. To meet this demand, an unwanted alternative could be the disturbance of natural ecosystems, which threatens natural processes that occur in soil, particularly affecting organic carbon (SOC). This SOC is vital in the maintenance of life in the world. The purpose of this research is to assess the status of SOC in the Great Clay Belt region of Northern Ontario, quantify its distribution and backward-predicting its change. Results showed that SOC predictions collected with a novel sampling approach performed better than existing soil data. Also, the use of space-for-time analysis was capable of detecting spatiotemporal changes in SOC from 1990 to 2020. This research project made use of digital soil mapping techniques and laboratory analysis. Information generated in this study could help to explore the potential of extending agricultural production while sustaining our environment.

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 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 score0.458
Threshold uncertainty score0.796

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 head0.011
GPT teacher head0.194
Teacher spread0.182 · 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 teacher head, 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
Published2021
Admission routes2
Has abstractyes

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