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Record W2237052110 · doi:10.6061/clinics/2015(12)02

Building a Lung Transplant Program

2015· editorial· en· W2237052110 on OpenAlexaboutno aff
Marcos Naoyuki Samano, Paulo Manuel Pêgo‐Fernandes

Bibliographic record

VenueClinics · 2015
Typeeditorial
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePulmonologistsLung transplantationLungSurgeryComplicationSepsisAnastomosisTransplantationGeneral surgeryInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Twenty-five years have passed since the first lung transplant was performed at the Instituto do Coração (INCOR) do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo. On October 16th, 1990, a 26-year-old woman with severe pulmonary fibrosis and secondary pulmonary hyper-tension underwent a single left lung transplant but only survived for 12 days, dying due to sepsis and diffuse alveolar damage. This occurred several months after the first and second (1) lung transplants in Brazil and seven years after the first in the world, which had been performed by Dr. Cooper in Toronto (2). Over a five-year period, nine more cases were performed, with the longest post-operative survival being 4 years. Despite the dedication of all the personnel involved with the program at that time, seven patients were never discharged due to acute respiratory failure and infection.

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)0.007
metaresearch head score (Gemma)0.019
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.009
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0020.002
Research integrity0.0090.018
Insufficient payload (model declined to judge)0.0060.003

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 head0.046
GPT teacher head0.460
Teacher spread0.414 · 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
GenreEditorial

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
Published2015
Admission routes1
Has abstractyes

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