MétaCan
Menu
Back to cohort
Record W2344637926 · doi:10.3390/polym8050158

Polymeric Biodegradable Stent Insertion in the Esophagus

2016· review· en· W2344637926 on OpenAlexaff
Kai Yang, Chris D. Ling, Tianwen Yuan, Yueqi Zhu, Ying-Sheng Cheng, Wenguo Cui

Bibliographic record

VenuePolymers · 2016
Typereview
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsStentRestenosisMedicineDysphagiaEsophageal stentSurgeryEsophagus

Abstract

fetched live from OpenAlex

Esophageal stent insertion has been used as a well-accepted and effective alternative to manage and improve the quality of life for patients diagnosed with esophageal diseases and disorders. Current stents are either permanent or temporary and are fabricated from either metal or plastic. The partially covered self-expanding metal stent (SEMS) has a firm anchoring effect and prevent stent migration, however, the hyperplastic tissue reaction cause stent restenosis and make it difficult to remove. A fully covered SEMS and self-expanding plastic stent (SEPS) reduced reactive hyperplasia but has a high migration rate. The main advantage that polymeric biodegradable stents (BDSs) have over metal or plastic stents is that removal is not require and reduce the need for repeated stent insertion. But the slightly lower radial force of BDS may be its main shortcoming and a post-implant problem. Thus, strengthening support of BDS is a content of the research in the future. BDSs are often temporarily effective in esophageal stricture to relieve dysphagia. In the future, it can be expect that biodegradable drug-eluting stents (DES) will be available to treat benign esophageal stricture, perforations or leaks with additional use as palliative modalities for treating malignant esophageal stricture, as the bridge to surgery or to maintain luminal patency during neoadjuvant chemoradiation.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.053
GPT teacher head0.341
Teacher spread0.288 · 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 designOther design
Domainnot available
GenreReview

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

Citations12
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePolymersSame topicEsophageal and GI PathologyFrench-language works237,207