MétaCan
Menu
Back to cohort
Record W4387925661 · doi:10.55449/congea.14.23.xi-023

A INFLUÊNCIA DA CONTAMINAÇÃO DO CEMITÉRIO DE HUMAITÁ/AM EM ÁREAS ADJACENTES

2023· article· pt· W4387925661 on OpenAlexaff
Marcelo A. Soares, Luan Cavalcante, Harumy Noguchi, Mariana Souza

Bibliographic record

VenueAnais Congresso Brasileiro de Gestão Ambiental · 2023
Typearticle
Languagept
FieldEnvironmental Science
TopicGeography and Environmental Studies
Canadian institutionsImpact
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

A tradição de se enterrar pessoas, que tem origem na cultura judaico-cristão, foi muito usada e continua a ser nos dias atuais, embora seja uma forma tradicional de cuidar dos mortos e honrar suas memórias, essa prática pode causar grande potencial de impacto ambiental e prejuízo à saúde da população das áreas adjacentes, causando a contaminação do solo por necrochorume que acaba chegando às águas subterrâneas.Desta forma, o referido trabalho tem como objetivo analisar se as áreas que se encontram próximas ao cemitério estão sendo afetadas pela pluma de contaminação.Para tanto, foram realizados estudos de embasamento científico e teórico, e uma visita ao cemitério municipal de Humaitá-AM para se analisar a construção do mesmo, sua localização e áreas adjacentes que podem estar sendo contaminadas.Observou-se alguns pontos que não estão de acordo com o estabelecido na legislação ambiental, e o cemitério apresenta algumas falhas em sua construção e disposição.Contudo, é evidente o risco à saúde da população de áreas adjacentes, por esses contaminantes de acordo com a literatura e com as normas estabelecidas na legislação ambiental.

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 score0.056
Threshold uncertainty score0.112

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 studies0.0020.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.256
Teacher spread0.236 · 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 routes1
Has abstractyes

Explore more

Same venueAnais Congresso Brasileiro de Gestão AmbientalSame topicGeography and Environmental StudiesFrench-language works237,207