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Record W2790070430 · doi:10.14745/ccdr.v43i05a02

Developing a vaccine for Haemophilus influenzae serotype a: Proceedings of a workshop

2017· article· en· W2790070430 on OpenAlexafffundvenueabout
Andrew D. Cox, L Barreto, Marina Ulanova, MG Bruce, RSW Tsang

Bibliographic record

VenueCanada Communicable Disease Report · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsLakehead UniversityNOSM UniversityPublic Health Agency of CanadaNational Research Council Canada
FundersCanadian Institutes of Health ResearchPublic Health AgencyPublic Health Agency of Canada
KeywordsIndigenousPublic healthHealth careAgency (philosophy)Political scienceClinical trialMedicineEnvironmental healthNursing

Abstract

fetched live from OpenAlex

serotype a (Hia) to examine the current state of disease epidemiology and a potential vaccine solution path. The meeting included representatives from academia, federal and territorial public health units, hospital laboratories, federal departments involved in Aboriginal health, advocacy organizations for Indigenous peoples and industry. Representatives from industry confirmed having the capacity and the interest to support preparation of clinical trial batches. Canadian regulatory authorities have expressed a willingness to help ensure appropriate measures are in place for licensure purposes. Furthermore, there is the capacity and interest in performing some clinical trials in Indigenous communities in both Canada and Alaska. Recommendations for next steps included: complete pre-clinical studies, improve epidemiological surveillance to better understand the extent of the disease in the rest of North America and globally, establish engagement mechanisms with national Indigenous organizations to ensure their peoples are fully involved in the process and explore funding opportunities to prepare clinical lots and undertake clinical trials.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.039
GPT teacher head0.295
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations29
Published2017
Admission routes4
Has abstractyes

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