OESTADODAARTE DE COMPOSTOS CARBONÍLICOSVOLÁTEISEMAMBIENTES INTERNOS:IMPACTOSÀ SAÚDEEMETODOLOGIAS DEAMOSTRAGEMEANÁLISES
Bibliographic record
Abstract
THE STATE OF THE ART OF VOLATILE CARBONYL COMPOUNDS IN INTERNAL ENVIRONMENTS: IMPACTS TO HEALTH AND SAMPLING METHODOLOGIES AND ANALYSIS. The primary sources of emission of volatile carbonyl compounds (CCs) in indoor environments are chipboard panels, laminate floors, plywood, paints and solvents, household products, fiberglass, gas stoves, heaters and heating systems. Several studies have already confirmed an indoor/outdoor (I/O) ratio greater than 1 (one) for several CCs, indicating that these compounds are emitted mainly from internal sources. CCs (especially aldehydes and ketones) are easily absorbed into the airways, presenting a considerable mutagenic, teratogenic and carcinogenic risk to humans. Therefore, this study aimed to review the CCs found in different indoor environments, the effects and impacts of these compounds on human health and the national and international guidelines that establish their maximum exposure limits. The methodologies most used in the literature to analyze CCs in the air were reviewed directly (in real-time) or indirectly (using pre-treatment steps). A detailed review of the sampling techniques: with and without adsorption, with and without derivatization, with adsorption and derivatization simultaneously; using various methodologies employed during the last decades (cartridges, filters, tubes or liquid absorbent-impinger) was carried out. Finally, this work describes the instrumental methods and the advantages and disadvantages of determining CCs individually and simultaneously in the atmosphere.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".