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Record W4386299373 · doi:10.38087/2595.8801.167

UMA ANÁLISE DA PERCEPÇÃO DA LOGÍSTICA REVERSA NO DESCARTE DE MEDICAMENTOS DOMICILIARES

2022· article· pt· W4386299373 on OpenAlexaff
Ísis Terezinha Santos de Santana, Jhonata Jankowitsch

Bibliographic record

VenueCOGNITIONIS Scientific Journal · 2022
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsImpact
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Este trabalho tem como escopo analisar as percepções sobre a logística reversa no que se refere ao descarte de medicamentos domiciliares, destacando o nível de conhecimento da população sobre os locais adequados e os impactos dos descartes inadequados desses fármacos. O referencial teórico expõe conceitos sobre devolução ou logística reversa, logística reversa e a legislação de descarte de medicamentos, e o impacto do descarte de medicamentos no bem-estar populacional e no meio ambiente. O método aplicado foi uma pesquisa exploratória e um estudo de caso na localidade de Taboão da Serra/SP. Foram entrevistadascento e vinte (120) pessoas, que responderam presencialmente quinze questões, previamente aprovadas pela CEP. A verificação dos dados foi decomposta em duas partes: determinação do perfil dos respondentes e percepção destes sobre o teor da pesquisa. As deliberações atingidas mostram a escassez de meios para o descarte adequado desses fármacos, a educação ambiental diminuta, e o desprovimento de uma consciência ambiental que dificulta o cumprimento das leis sobre o descarte correto de medicamentos prescritos.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.259
Teacher spread0.237 · 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
Published2022
Admission routes1
Has abstractyes

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