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Record W2795603895 · doi:10.1684/mst.2018.0758

2nd Doctors Without Borders Pediatric Days, Dakar December 15-16, 2017

2018· article· fr· W2795603895 on OpenAlexaff
Ayesha Kadir, Laurent Hiffler, Sahar Nejat, Daniel Martínez García

Bibliographic record

VenueMédecine et Santé Tropicales · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPediatricsMedicineMedical emergency

Abstract

fetched live from OpenAlex

SF Paediatric Days est une rencontre visant a `ame ´liorer la qualite ´des soins pe ´diatriques dans les contextes humanitaires.A `notre connaissance, c'est la seule rencontre existante en pe ´diatrie humanitaire.Les secondes journe ´es se sont de ´roule ´es a ` Dakar, au Se ´ne ´gal, du 15 au 16 de ´cembre 2017, et ont re ´uni 210 participants de 53 pays, dont des membres du personnel de terrain et du sie `ge de MSF, des experts universitaires et des colle `gues non-MSF travaillant dans des contextes humanitaires.Les principaux sujets aborde ´s e ´taient l'asphyxie pe ´rinatale, les soins critiques en neurologie pe ´diatrique, la prise en charge de la douleur et les soins palliatifs.

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.255
Threshold uncertainty score0.852

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.2550.065

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 head0.042
GPT teacher head0.418
Teacher spread0.376 · 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
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".

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Citations0
Published2018
Admission routes1
Has abstractno

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