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A Novel Model for Post-Transplant Obliterative Airway Disease Reveals Angiogenesis from the Pulmonary Circulation

2005· article· en· W2079137031 on OpenAlexafffund
André Dutly, C Andrade, Ryan Verkaik, Lakshmi Kugathasan, Judy Trogadis, Mingyao Liu, Thomas K. Waddell, Duncan J. Stewart, Shaf Keshavjee

Bibliographic record

VenueAmerican Journal of Transplantation · 2005
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of TorontoSt. Michael's HospitalToronto General Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineAirwayParenchymaAngiogenesisTransplantationLung transplantationLungDiseasePathologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

We present a novel animal model for post-transplant obliterative airway disease in which the donor trachea is implanted into the recipient's lung parenchyma. Although this procedure is technically more challenging than the heterotopic model of implantation into a subcutaneous pouch, it has several important advantages some of which are the appropriate local environment and the possibility of local immunosuppressive therapy after transtracheal gene, cell or drug delivery. This model has revealed new insights into angiogenic potential of the pulmonary circulation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.305
Teacher spread0.280 · 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 designBench or experimental
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

Citations39
Published2005
Admission routes2
Has abstractno

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