MétaCan
Menu
Back to cohort
Record W3023230572 · doi:10.14393/rcg217442492

ANÁLISE DA EVOLUÇÃO TEMPORAL DO USO E COBERTURA DA TERRA NA BACIA DO RIBEIRÃO DA LAJE, NO SUDOESTE DE GOIÁS, DE 1987 A 2017

2020· article· pt· W3023230572 on OpenAlexfundno aff
Wellmo dos Santos Alves, Alécio Perini Martins, Irací Scopel

Bibliographic record

VenueCaminhos de Geografia · 2020
Typearticle
Languagept
FieldEnvironmental Science
TopicGeography and Environmental Studies
Canadian institutionsnot available
FundersPartenariat Canadien Contre Le Cancer
KeywordsGeographyPhysics

Abstract

fetched live from OpenAlex

O modelo de produção, principalmente a partir da revolução industrial, muitas vezes sem considerar a conservação dos recursos naturais para atender à demanda de uma população mundial crescente, tem causado desequilíbrios ecológicos (perda da biodiversidade, impactos negativos nos solos e recursos hídricos, entre outros).Assim, objetivou-se entender as mudanças do uso e cobertura da terra na bacia do ribeirão da Laje, de 1987 a 2017.Esse recurso é importante para diversos usos múltiplos na microrregião Sudoeste de Goiás, sendo uma das principais fontes de água para o abastecimento público da população de Rio Verde (GO).Com o uso de geotecnologias, foram gerados os produtos cartográficos e obtidos dados quantitativos, estes analisados utilizando a técnica de matriz de transição.Foram observados, principalmente: substituição significativa de pastagem por área de agricultura; diminuição da vegetação de Cerrado; expansão da área urbana, industrial, de construção rural e represas; e extensas áreas com erosão laminar e em sulco, principalmente associadas à pastagem degradada.Esses dados indicam a necessidade de políticas públicas comprometidas com o desenvolvimento econômico condizente com a sustentabilidade ambiental.Esse trabalho irá subsidiar o planejamento e a gestão ambiental dessa bacia hidrográfica e servirá de base para outros estudos.

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)0.001
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 score0.283
Threshold uncertainty score0.563

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.228
Teacher spread0.210 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCaminhos de GeografiaSame topicGeography and Environmental StudiesFrench-language works237,207