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Animal testing for vaccines. Implementing replacement, reduction and refinement: challenges and priorities

2020· article· en· W3091934739 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiologicals · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsHealth Canada
FundersInnovative Medicines InitiativeHumane Society InternationalEuropean Federation of Pharmaceutical Industries and AssociationsBill and Melinda Gates Foundation
KeywordsHarmonizationStandardizationAllianceConsistency (knowledge bases)Work (physics)BusinessMedicinePolitical scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Transition to in vitro alternative methods from in vivo in vaccine release testing and characterization, the implementation of the consistency approach, and a drive towards international harmonization of regulatory requirements are most pressing needs in the field of vaccines. It is critical for global vaccine community to work together to secure effective progress towards animal welfare and to ensure that vaccines of ever higher quality can reach the populations in need in the shortest possible timeframe. Advancements in the field, case studies, and experiences from Low and Middle Income Countries (LMIC) were the topics discussed by an international gathering of experts during a recent conference titled "Animal Testing for Vaccines - Implementing Replacement, Reduction and Refinement: Challenges and Priorities". This conference was organized by the International Alliance for Biological Standardization (IABS), and held in Bangkok, Thailand on December 3 and 4 2019. Participants comprised stakeholders from many parts of the world, including vaccine developers, manufacturers and regulators from Asia, Europe, North America, Australia and New Zealand. In interactive workshops and vibrant panel discussions, the attendees worked together to identify the remaining barriers to validation, acceptance and implementation of alternative methods, and how harmonization could be promoted, especially for LMICs.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.072
GPT teacher head0.308
Teacher spread0.236 · 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