MétaCan
Menu
Back to cohort

A report on the development of COVID-19 guidelines for rehabilitation professionals in African settings

2021· article· en· W3128687513 on OpenAlexaff
Etienne Ngeh Ngeh, Nnenna Chigbo, Zillah Whitehouse, Emelie Moris Anekwu, Lela Mukaruzima, Lungile Mtsetfwa, Rogers Kitur, Mary Wetani Agoriwo, Priscillah Ondoga, Lynn Cockburn

Bibliographic record

VenuePan African Medical Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineRehabilitationGuidelineCoronavirus disease 2019 (COVID-19)Disease2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MEDLINEIntensive care medicinePhysical therapyNursingInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

COVID-19 is the disease caused by SARS-CoV-2, one of a large family of coronaviruses. Severe forms of the disease can lead to respiratory failure with multiple organ failure necessitating rehabilitation in both acute and long-term care. With the increasing prevalence of COVID-19 and rehabilitation needs, the African Rehabilitation Network (AFRENET) produced a guidance document to assist in reducing variation in clinical practice among rehabilitation professionals in the Africa Region. This report outlines the process of the guideline development.

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)0.010
metaresearch head score (Gemma)0.234
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.594
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.234
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 integrity0.0000.001
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 head0.049
GPT teacher head0.409
Teacher spread0.360 · 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.

Study designNot applicable
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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePan African Medical JournalSame topicLong-Term Effects of COVID-19French-language works237,207