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Record W6969400676 · doi:10.5281/zenodo.8060930

Questions et réponses pour Atelier 2023: La bilharziose génitale chez la femme (BGF)

2023· article· fr· W6969400676 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languagefr
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsBruyère
Fundersnot available
KeywordsFemale circumcisionLigneHealth professionalsSchistosomiasis

Abstract

fetched live from OpenAlex

<strong>Questions et réponses pour Atelier 2023: La bilharziose génitale chez la femme (BGF) </strong> L<strong>'</strong>Atelier 2023 : La bilharziose génitale chez la femme (BGF) s'est déroulée en ligne du 4 au 19 mai 2023. L'atelier a été mené par Bridges to Development en partenariat avec La Fondation Apprendre Genève et avec le soutien du End Fund. Plus de 200 professionnels de la santé d'Afrique subsaharienne y ont participé. Ils ont été formés à pour améliorer leurs compétences au niveau, du diagnostic et du traitement de la BGF. Les questions présentées dans ce document ont été formulées par les participants à l'atelier. L'équipe d'experts en la matière qui a soutenu la formation a fourni les réponses. Il s'agit d'un document évolutif, qui fait l'objet de mises à jour et de révisions. Pour votre référence, lisez la version 1 élaborée le 19 mai 2023. Bridges to Development apporte une expertise sujet et des partenariats, avec une équipe qui a des décennies d'expérience en matière de collaborations internationales. Depuis 2021, Bridges travaille en partenariat avec la Fondation Apprendre Genève, utilisant "l'approche Scholar", un ensemble unique d'interventions recherchées, développées et mises en œuvre par la Fondation pour soutenir l'apprentissage par les pairs. <strong>Questions and answers for Workshop 2023: Female genital schistosomiasis (FGS)</strong> Workshop 2023: Female Genital Schistosomiasis (FGS) took place online from May 4 to 19, 2023. The workshop was conducted by Bridges to Development in partnership with The Geneva Learning Foundation and with the support of the End Fund. Over 200 healthcare professionals from sub-Saharan Africa took part. They were trained to improve their skills in diagnosing and treating FGS. The questions presented in this document were formulated by workshop participants. The team of subject matter experts who supported the training provided the answers. This is a living document, subject to updates and revisions. For your reference, read version 1 developed on May 19, 2023. Bridges to Development brings subject matter expertise and partnerships with others around the world, reflected in a team that brings decades of experience with international collaborations. Since 2021, Bridges has worked in partnership with The Geneva Learning Foundation, using the “Scholar approach”, the unique package interventions researched, developed, and implemented by the Foundation to support peer learning.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0550.234

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 head0.045
GPT teacher head0.314
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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