MétaCan
Menu
Back to cohort
Record W2787328205 · doi:10.1155/2018/5202173

Pulmonary Alveolar Proteinosis in Setting of Inhaled Toxin Exposure and Chronic Substance Abuse

2018· article· en· W2787328205 on OpenAlexaff
Meirui Li, Salem Alowami, Miranda Schell, C. Davis, Asghar Naqvi

Bibliographic record

VenueCase Reports in Pulmonology · 2018
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPulmonary alveolar proteinosisMedicineAlveolar macrophageHypoxemiaLungMacrophagePathologyImmunologyPhysiologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Pulmonary alveolar proteinosis (PAP) is a rare lung disorder in which defects in alveolar macrophage maturation or function lead to the accumulation of proteinaceous surfactant in alveolar space, resulting in impaired gas exchange and hypoxemia. PAP is categorized into three types: hereditary, autoimmune, and secondary. We report a case of secondary PAP in a 47-year-old man, whose risk factors include occupational exposure to inhaled toxins, especially aluminum dust, the use of anabolic steroids, and alcohol abuse, which in mice leads to alveolar macrophage dysfunction through a zinc-dependent mechanism that inhibits granulocyte macrophage-colony stimulating factor (GM-CSF) receptor signalling. Although the rarity and vague clinical presentation of PAP can pose diagnostic challenges, clinician awareness of PAP risk factors may facilitate the diagnostic process and lead to more prompt treatment.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.334
Teacher spread0.308 · 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 designCase report
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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCase Reports in PulmonologySame topicNeonatal Respiratory Health ResearchFrench-language works237,207