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Record W4385262376 · doi:10.53141/peqacp.2023.3.as1

Ambiente e Salute News n.20 - marzo-aprile 2023

2023· article· en· W4385262376 on OpenAlexaff
Giacomo Toffol, Angela Biolchini, Luisa Bonsembiante, Vinceza Briscioli, Laura Brusadin, Sabrina Bulgarelli, Elena Caneva, Ilaria Mariotti, Federico Marolla, Aurelio Nova, Angela Pasinato, Giuseppe Primavera, Laura Reali, Annamaria Sapuppo, Laura Todesco, Elena Uga, Anna Valori, Luisella Zanino

Bibliographic record

VenueQUADERNI ACP · 2023
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsResidenceAir quality indexPopulationAgency (philosophy)Quality (philosophy)Environmental healthEnvironmental planningGeographyBusinessEnvironmental scienceMeteorologyMedicineDemographySociology

Abstract

fetched live from OpenAlex

The European Environment Agency (EEA) has recently developed the European Environment and Health Atlas: an online platform [1] to reveal the air quality where we live, noise levels, green areas, and the quality of bathing sites. It is one of the tools set up by EEA to monitor the quality of the environment in Europe as part of policies to achieve zero pollution. It will be updated regularly and is open to user feedback. It is possible to obtain information on the air quality in our environment by clicking on a map or entering our address, thus obtaining indications of annual averages for PM2.5 , NO2 and Ozone and displaying the concentration of the pollutants as well as the number of people exposed to them, the number of preventable premature deaths and the number of life years lost. There is also the measure of noise monitoring level (not available for Italian locations), bathing water quality and the green area closest to your residence. In this issue of Environment and Health news there are various articles of the effects of air pollution on the vulnerable population (pregnant women and children), so the atlas is an excellent way to learn about the quality of the air we breathe every day in the places where we live and work. In this journal we continue to summarize the main articles published in the monitored journals, all articles and editorials deemed worthy of attention are listed divided by topic, with a brief commentary. This issue is based on the systematic monitoring of publications in March and April 2023.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.439
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.055

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 head0.074
GPT teacher head0.416
Teacher spread0.342 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueQUADERNI ACPSame topicNoise Effects and ManagementFrench-language works237,207