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Record W4386761814 · doi:10.1002/9781119633884.ch2

Historical Developments that Facilitated Lung Transplantation

2023· other· en· W4386761814 on OpenAlexaboutno aff
Stephen Chiu, Ankit Bharat, G. Alexander Patterson

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLung transplantationTransplantationAnastomosisDehiscenceImmunosuppressionSurgeryLungBronchopulmonary dysplasiaGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

The first documented attempts of transplantation of the lung involved feline heterotopic en-bloc heart–lung into the neck by Alexis Carrel in 1907. In August 1968, Denton Cooley performed the first heart–lung transplantation in Houston, Texas, in a two-month-old infant with a complete atrioventricular canal defect and concomitant pulmonary hypertension. To better understand the factors contributing to bronchial anastomotic dehiscence, investigators at the University of Toronto performed a series of studies using a canine model of lung transplantation. The target of these investigations was to understand the effects of immunosuppression and ischemia on healing of the bronchial anastomosis. Vaughn Starnes and colleagues at the University of Stanford in late 1990 performed the first successful living-donor lobar transplantation, transplanting a mother's right upper lobe into her 12-year-old daughter suffering from bronchopulmonary dysplasia.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0070.002

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 head0.058
GPT teacher head0.332
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

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