MétaCan
Menu
Back to cohort
Record W4206394992 · doi:10.1002/pul2.12031

Building a dedicated pediatric pulmonary hypertension program: A consensus statement from the pediatric pulmonary hypertension network

2022· article· en· W4206394992 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePulmonary Circulation · 2022
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsStollery Children's HospitalUniversity of Alberta
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsMedicinePulmonary hypertensionIntensive care medicineStatement (logic)Consensus conferenceCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Pediatric pulmonary hypertension (PH) is a severe, life-threatening disease associated with diverse cardiac, pulmonary, and systemic disorders, which generally requires expertise from multiple disciplines for management. Unfortunately, expert centers are limited, often due to inadequate resources or unfamiliarity with needed components for success. The Pediatric Pulmonary Hypertension Network (PPHNet) includes expert centers in North America specifically dedicated to advancing the field of pediatric PH through research and excellent clinical care. PPHNet member sites were queried for valuable program components and these findings were discussed for consensus. Here we provide a collective overview of key elements of an optimal pediatric PH program: team composition, access to services, and commitment to education. It is our intention that this document will assist newer and/or smaller programs identify avenues and resources for growth and provide avenues for collaboration.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.286
Teacher spread0.246 · 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