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Record W4390746059 · doi:10.3389/fitd.2023.1297109

Making clinical trials a public norm for health decisions in sub-Saharan Africa

2024· article· en· W4390746059 on OpenAlexaff
Sélidji Todagbé Agnandji, Marguerite Massinga Loembé, Armel V. N. Mbouna, Fallowne Mbadinga, Paulin N. Essone, Ghyslain Mombo‐Ngoma, Rose G. F. Leke, Yvonne K. Mburu, Jean‐Jacques Muyembé‐Tamfum, Jean‐Marie Okwo‐Bele, Samba O. Sow, Charles Shey Wiysonge, Alimuddin Zumla, Ayôla Akim Adégnika, Michael Ramharter, Peter G. Kremsner, Pierre‐Blaise Matsiegui, Yap Boum, Francine Ntoumi

Bibliographic record

VenueFrontiers in Tropical Diseases · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsNorm (philosophy)Public healthPolitical scienceClinical trialPsychologyMedicineNursingLawPathology

Abstract

fetched live from OpenAlex

A clinical trial is intrinsically a collaborative undertaking. The complex steps, including identifying the biological mechanisms, discovering products, preclinical studies, and the clinical development from phase 1 to 3 clinical trials allowing market authorisation of a product, are unlikely to be feasible for a single institution or a country alone. Collaboration is therefore necessary to establish and maintain the research and innovation that is a prerequisite to tackle health threats, irrespective of the socioeconomic status of the countries (1).

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)0.002
metaresearch head score (Gemma)0.013
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 score0.801
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.013
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)0.0000.000

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 head0.218
GPT teacher head0.475
Teacher spread0.257 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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