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Record W2062527887 · doi:10.1002/ajim.20589

Dust content of lungs and its relationships to pathology, radiology and occupational exposure in Ontario hardrock miners

2008· article· en· W2062527887 on OpenAlexafffundabout
Dave K. Verma, A. C. Ritchie, D. C. F. Muir

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversity of TorontoMcMaster University
FundersWorkplace Safety and Insurance Board
KeywordsSilicosisMedicinePneumoconiosisHydroxyprolinePathologyLymphLungPathologicalFibrosisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Autopsied lungs from 29 hard rock miners were investigated to determine the relationship of the dust content to pathology, radiology, and occupational exposure. METHODS: Each lung was divided horizontally into three sections. Pathological and radiological studies and chemical analyses were carried out on samples from each section. The hilar lymph nodes were also studied chemically. The work history and smoking history were assessed. The occupational exposure to silica and total dust were estimated. The effect of smoking was examined, and the relationship between dust content of the lungs to that of the lymph nodes were also investigated. RESULTS: There was a good agreement between radiologic and pathologic findings. Positive correlations were seen between hydroxyproline (as an index of fibrosis), silica dust, non-silica inorganic dust, radiographic category of pneumoconiosis and pathologic grade of silicosis. Smokers lost on average 7 years of life compared to non-smokers, but numbers were small and no adjustment was made. Silica appeared to be concentrated in lungs and lymph nodes compared to the estimates of silica concentration in the mining environment. Silica in the lymph nodes on average is 2.4-fold higher than in the lungs. CONCLUSIONS: This study of autopsied hard rock miners lungs shows positive relationships between lung dust and hydroxyproline content, radiological and pathological findings.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

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

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 head0.121
GPT teacher head0.280
Teacher spread0.159 · 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.

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

Citations20
Published2008
Admission routes3
Has abstractyes

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