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Contributions of the Transplant Registry: The 2006 Annual Report of the North American Pediatric Renal Trials and Collaborative Studies (NAPRTCS)*

2007· article· en· W2147664035 on OpenAlexaffabout
Jodi M. Smith, Donald M. Stablein, Ricardo Muñoz, Diane Hébert, Ruth A. McDonald

Bibliographic record

VenuePediatric Transplantation · 2007
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineTransplantationClinical trialRenal transplantKidney transplantationIntensive care medicinePediatricsFamily medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

This summary of the NAPRTCS 2006 Annual Report of the Transplant Registry highlights the significant impact the registry has had in advancing knowledge in pediatric renal transplantation worldwide. This cooperative group has collected clinical information on children undergoing a renal transplantation since 1987 and now includes over 150 participating medical centers in the USA, Canada, Mexico, and Costa Rica. Currently, the NAPRTCS transplant registry includes information on 9837 renal transplants in 8990 patients (NAPRTCS 2006 Annual Report). Since the first data analysis in 1989, NAPRTCS reports have documented marked improvements in outcome after renal transplantation in addition to identifying factors associated with both favorable and poor outcomes. The registry has served to document and influence practice patterns, clinical outcomes, and changing trends in renal transplantation.

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)0.125
metaresearch head score (Gemma)0.156
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.661

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1250.156
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.009
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.332
Teacher spread0.311 · 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 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

Citations479
Published2007
Admission routes2
Has abstractyes

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