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Record W2441115433 · doi:10.5902/2179460x21919

AVALIAÇÃO DA GESTÃO DOS RESÍDUOS SÓLIDOS DE SAÚDE DA IRMANDADE SANTA CASA DE CARIDADE DE SÃO GABRIEL-RS SOB A ÓTICA DA NOVA LEGISLAÇÃO BRASILEIRA

2016· article· en· W2441115433 on OpenAlexaff
Ana Paula da Motta Pereira, Beatriz Stoll Moraes

Bibliographic record

VenueCiência e Natura · 2016
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsImpact
Fundersnot available
KeywordsLegislationBusinessPolitical scienceMunicipal solid wasteWelfare economicsEngineeringLawWaste management

Abstract

fetched live from OpenAlex

The increasing awareness about the risks on public health and environment, caused by solid residues generated by health service, is mainly due to its infectious fractions. In Brazil, there's thousand health units producing these residues and, in most cities, the handling issue and final arrangement are not yet resolved. The Irmandade da Santa Casa of São Gabriel, RS, acknowledging its responsability as generator of health residues sought to adjust to the legislation and minimize the impacts caused on the environment and others afected by its activities. Thus, the present study sought to, through exploratory research, analyze the conditions of the management of solid wastes on health services which are produced by Irmandade da Santa Casa in order to verify the compliance with the existing legal standards. The present study used the resolution of the executive board ( DC ) 306/2004 of the National Health Surveillance Agency ( ANVISA ), the Resolution 358/2005 of the National Environment Council ( CONAMA ) , and 2010 12.305 law which establishes the national policy on solid waste to evaluate and compare the reality of the institution. Through research it was possible to identify strengths and weaknesses on the management of waste as well as some necessary adjustments based on the current legislation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.320
Teacher spread0.278 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

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