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Record W4387395280 · doi:10.56238/uniknowindevolp-138

Evaluation of the Level of Air Pollution by Gases and Particulates at the Edge and in the Interior of a Conservation Unit: A Case Study in the FLONA of Restinga de Cabedelo, Paraíba, Brazil

2023· book-chapter· en· W4387395280 on OpenAlexaff
José Frankneto da Silva Cordeiro, Bruna D'Ângela de Souza, Washington Luiz Pinto Filho, Ellen Kathia Tavares Batista, Maria Betânia de Almeida Oliveira, Alcidney Batista Celeste, Dácio Vales Lacerda, Cacildo de Medeiros Brito Cavalcante

Bibliographic record

VenueSeven Editora eBooks · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsTransport Canada
Fundersnot available
KeywordsParticulatesAir pollutionEnvironmental scienceAir quality indexPollutionPollutantUnit (ring theory)Environmental engineeringAir pollutantsEnvironmental protectionWork (physics)Atmosphere (unit)Environmental planningWaste managementEngineeringGeographyMeteorologyChemistryEcology

Abstract

fetched live from OpenAlex

Air pollution has become one of the biggest problems and concerns worldwide, especially in large industrial cities, where the discharges of toxic substances together with the intense and growing traffic of vehicles are largely responsible for the emission of pollutants into the atmosphere. It is known that road infrastructure generates several environmental impacts during its implementation and operation. Thus, the present study seeks to describe the air quality in and around the Restinga de Cabedelo National Forest (Flona), a conservation unit located in the State of Paraíba, prior to the improvement work with expansion of the capacity and safety of the BR-230 Highway, through the measurement of PTS, PM10, SO2 and NO2.

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)0.000
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 score0.129
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.307
Teacher spread0.216 · 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

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