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Record W27239056 · doi:10.1111/petr.12729

Investigating the stress on wheels and rails

2011· article· en· W27239056 on OpenAlexfundno aff
Otto Kleiner, Christian Schindler

Bibliographic record

VenuePediatric Transplantation · 2011
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsnot available
FundersCanadian Association for the Study of the Liver
KeywordsFinite element methodWorkstationDisplacement (psychology)Stress (linguistics)Computer scienceEngineeringSimulationMechanical engineeringStructural engineering

Abstract

fetched live from OpenAlex

Routine use of transanastomotic biliary stents (RTBS) for biliary reconstruction in liver transplantation (LT) is controversial, with conflicting outcomes in adult randomized trials. Pediatric literature contains limited data. This study is a retrospective review of 99 patients who underwent first LT (2005-2014). In 2011, RTBS was discontinued at our center. This study describes biliary complications following LT with and without RTBS. 56 (56%) patients had RTBS. Median age at LT was 1.9 yr (IQR 0.7, 8.6); 55% were female. Most common indication for LT was biliary atresia (36%). Most common biliary reconstruction was Roux-en-Y choledochojejunostomy (75% with RTBS, 58% without RTBS, p = 0.09). Biliary complications (strictures, bile leaks, surgical revision) occurred in 23% without significant difference between groups (20% with RTBS, 28% without RTBS, p = 0.33). Patients with RTBS had routine cholangiography via the tube at 6-8 wk; thus, significantly more patients with RTBS had cholangiograms (91% vs. 19%, p < 0.0001). There was no difference in the number of patients who required therapeutic intervention via endoscopic or percutaneous transhepatic cholangiography (11% with RTBS, 19% no RTBS, p = 0.26). Routine use of RTBS for biliary reconstruction in pediatric LT may not be necessary, and possibly associated with need for costlier, invasive imaging without improvement in outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.184
Teacher spread0.172 · 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.

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

Citations1
Published2011
Admission routes1
Has abstractyes

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