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Record W4378978658 · doi:10.1055/s-0043-1769614

The Global Burden of Pleural Diseases

2023· article· en· W4378978658 on OpenAlexaff
Erik Vakil, Niloofar Taghizadeh, Alain Tremblay

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsAlberta Health ServicesAlberta HealthUniversity of Calgary
Fundersnot available
KeywordsMedicineBurden of diseaseIntensive care medicineDiseasePneumothoraxTuberculosisDisease burdenPleural effusionPleural diseaseQuality of life (healthcare)PneumoniaEnvironmental healthMalignant pleural effusionRespiratory diseaseSurgeryInternal medicinePathologyLung

Abstract

fetched live from OpenAlex

Pleural diseases include a spectrum of disorders broadly categorized into pneumothorax and pleural effusion. They often cause pain, breathlessness, cough, and reduced quality of life. The global burden of diseases reflects regional differences in conditions and exposures associated with pleural disease, such as smoking, pneumonia, tuberculosis, asbestos, cancer, and organ failure. Disease burden in high-income countries is overrepresented given the availability of data and disease burden in lower-income countries is likely underestimated. In the United States, in 2016, there were 42,215 treat-and-discharge visits to the emergency room for pleural diseases and an additional 361,270 hospitalizations, resulting in a national cost of $10.1 billion.

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)0.002
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 score0.125
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.027
GPT teacher head0.345
Teacher spread0.317 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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