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Record W3021173586 · doi:10.4103/sjg.sjg_161_20

COVID-19 and endoscopy services in intermediately affected countries: a position statement from the saudi gastroenterology association

2020· review· en· W3021173586 on OpenAlexaff
Majid A. Almadi, AbdulrahmanM Aljebreen, Nahla Azzam, Nuha Alammar, EmadS Aljahdli, FahadI Alsohaibani, Resheed Alkhiari, AbdulazizO Almasoud, MohammadS Al Beshir, Suliman Alshankiti, Ahmad Alharbi, Mohammed Alkhathami, Faisal Batwa

Bibliographic record

VenueSaudi Journal of Gastroenterology · 2020
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsHealth carePandemicPersonal protective equipmentCoronavirus disease 2019 (COVID-19)MedicineRationingInfection controlMedical emergencyBusinessFamily medicineDiseaseInfectious disease (medical specialty)Internal medicineIntensive care medicinePolitical science

Abstract

fetched live from OpenAlex

With the global pandemic due to coronavirus disease 2019 (COVID-19), there has been a significant strain on healthcare facilities. The infectivity rate, as well as the rate of healthcare workers who have fallen ill to the disease, has raised concerns globally on the proper management of patients as well as the role of safe healthcare provision utilizing personal protective equipment (PPE). Furthermore, the limited supply of PPEs has mandated rationing their use to achieve maximum utility and preservation. Multiple gastroenterology associations have issued guidance and statements that would help healthcare providers in navigating these unprecedented and difficult times, and the Saudi Gastroenterology Association has provided this statement in an effort to bring the most up to date information for the management of endoscopy units in terms of resources, manpower planning, scheduling, as well as infection control policies and leadership.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.317
Teacher spread0.300 · 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 designNot applicable
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

Citations11
Published2020
Admission routes1
Has abstractyes

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