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Record W3164387215 · doi:10.1055/s-0041-1727250

Mycobacteria: Selection of Transplant Candidates and Post–lung Transplant Outcomes

2021· article· en· W3164387215 on OpenAlexaff
Daniel Friedman, Karen Doucette

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineTuberculosisNontuberculous mycobacteriaEpidemiologyLung transplantationDiseaseIntensive care medicinePopulationMycobacterium tuberculosisLung diseaseLeprosyImmunologyAntimicrobialLungMycobacteriumPathologyInternal medicineMicrobiologyEnvironmental healthBiology

Abstract

fetched live from OpenAlex

is a large, clinically relevant bacterial genus made up of the agents of tuberculosis and leprosy and hundreds of species of saprophytic nontuberculous mycobacteria (NTM). Pathogenicity, clinical presentation, epidemiology, and antimicrobial susceptibilities are exceptionally diverse between species. Patients with end-stage lung disease and recipients of lung transplants are at a higher risk of developing NTM colonization and disease and of severe manifestations and outcomes of tuberculosis. Data from the past three decades have increased our knowledge of these infections in lung transplant recipients. Still, there are knowledge gaps to be addressed to further our understanding of risk factors and optimal treatments for mycobacterial infections in this population.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.016
GPT teacher head0.320
Teacher spread0.304 · 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 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

Citations9
Published2021
Admission routes1
Has abstractyes

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