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Record W2978187066 · doi:10.37478/agr.v4i2.459

The Causes and Effects of Tropical Deforestation

2020· article· en· W2978187066 on OpenAlexaff
Leslie Campbell

Bibliographic record

VenueAGRICA · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRainforestDeforestation (computer science)Tropical rainforestTropicsTropical agricultureContext (archaeology)AgroforestryTemperate climateGeographyProductivitySubtropicsTemperate rainforestAgricultureTropical climateEcologyEnvironmental scienceEcosystemBiologyEconomics

Abstract

fetched live from OpenAlex

Tropical rainforest deforestation is a major problem in many tropical regions and can have major impacts on system ecology and long term soil productivity. This paper examines the trend of increased colonization of tropical rainforest regions and the resulting effects on long term natural system productivity in these areas. It also explores the impact of conventional agricultural practices, the majority of which were developed in temperate climates, when employed in a tropical context. International trends in the consumption of imported tropical wood and rainforest products are also suggested as a major culprit for increased tropical deforestation. Reduction in international rainforest product consumption and greater awareness on the part of Western consumers as to the impacts of tropical deforestation are suggested as potential solutions to reduce this problem.

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 score0.022
Threshold uncertainty score0.045

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.164
Teacher spread0.158 · 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
Published2020
Admission routes1
Has abstractyes

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