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Record W2005818186 · doi:10.1002/ppul.20973

Strategic plan for pediatric respiratory diseases research: An NHLBI working group report

2008· article· en· W2005818186 on OpenAlexaff
Steve Abman, Alan H. Jobe, Victor Chernick, Carol J. Blaisdell, Mario Castro, María I. Ramirez, James E. Gern, Garry R. Cutting, Greg Redding, James S. Hagood, Jeffrey A. Whitsett, J. Usha Raj, Robyn J. Barst, Gregory J. Kato, David Gozal, Gabriel G. Haddad, Nanduri R. Prabhakar, Estelle B. Gauda, Fernando D. Martínez, Robert I. Tepper, Robert E. Wood, Frank J. Accurso, W. Gerald Teague, José G. Venegas, F. Sessions Cole, Rosalind J. Wright

Bibliographic record

VenuePediatric Pulmonology · 2008
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsManitoba Beekeepers' Association
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsMedicineIntensive care medicineTranslational researchLungAsthmaPathologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

The Division of Lung Diseases of the National Heart, Lung and Blood Institute (NHLBI) recently held a workshop to identify gaps in our understanding and treatment of childhood lung diseases and to define strategies to enhance translational research in this field. Leading experts with diverse experience in both laboratory and patient-oriented research reviewed selected areas of pediatric lung diseases, including perinatal programming and epigenetic influences; mechanisms of lung injury, repair, and regeneration; pulmonary vascular disease (PVD); sleep and control of breathing; and the application of novel translational methods to enhance personalized medicine. This report summarizes the proceedings of this workshop and provides recommendations for emphasis on targeted areas for future investigation. The priority areas identified for research in pediatric pulmonary diseases included: (1) epigenetic and environmental influences on lung development that program pediatric lung diseases, (2) injury, regeneration, and repair in the developing lung, (3) PVD in children, (4) development and adaptation of ventilatory responses to postnatal life, (5) nonatopic wheezing: aberrant large airway development or injury? (6) strategies to improve assessment, diagnosis, and treatment of pediatric respiratory diseases, and (7) predictive and personalized medicine for children.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.377
GPT teacher head0.446
Teacher spread0.069 · 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.

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

Citations18
Published2008
Admission routes1
Has abstractyes

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