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Record W2101830685 · doi:10.1080/089583700196545

PULMONARY RESPONSES TO INHALED POORLY SOLUBLE PARTICULATE IN THE HUMAN

2000· review· en· W2101830685 on OpenAlexaff
Francis H. Y. Green

Bibliographic record

VenueInhalation Toxicology · 2000
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsParticulatesInhalationEnvironmental chemistryInhalation exposureMedicineChemistryEnvironmental scienceAnesthesiaOrganic chemistry

Abstract

fetched live from OpenAlex

This review focuses on the human pulmonary effects of talc, carbon black, coal dust, diesel exhaust, and titanium dioxide as examples of poorly soluble, nonfibrous particles (PSPs). Other particulates with similar characteristics (e.g., iron oxide) are included when considering the question of whether there is a characteristic human response to this class of compounds. The overall objective is to characterize the responses to these compounds using information from epidemiology, pathology, and cell biology so that comparisons with animal responses can be made. Exposure to PSPs is associated with two broad classes of disease in the human: pneumoconiosis and chronic obstructive lung disease. The basic pathologic features and pathogenesis of the different lesions associated with exposure to PSPs are described. This is followed by a review of the evidence linking exposure to coal, carbon black, diesel exhaust, talc, and titanium dioxide with these diseases. With the exception of diesel exhaust, which contains genotoxic constituents, PSPs have not been definitely linked to human lung cancer. Some questions relevant to this review are: 1. How does the human lung respond to PSPs? Specifically, (a) what are the morphologic features, and (b) what is their pathogenesis? 2. Is there evidence for clearance overload in the human, and if so, what are the characteristics of the associated tissue response? 3. Are PSPs associated with lung cancer in the human? 4. What are the major similarities and differences between human and rodent lung cancers? 5. Do inflammation, epithelial hyperplasia, and fibrosis play a role in the development of human lung cancer?

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.003

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 head0.126
GPT teacher head0.408
Teacher spread0.282 · 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
GenreReview

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

Citations25
Published2000
Admission routes1
Has abstractyes

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