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Record W3183609495

European biobanks in the coronavirus environment

2021· article· en· W3183609495 on OpenAlexaboutno aff
Judita Kinkorová

Bibliographic record

VenueBiopreservation and Biobanking · 2021
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
Fundersnot available
KeywordsBiobankPreparednessInternational Health RegulationsBusinessEuropean unionPandemicWork (physics)Coronavirus disease 2019 (COVID-19)Political scienceEnvironmental planningGeographyMedicineEngineeringInternational tradeLawBiologyDiseaseBioinformatics
DOInot available

Abstract

fetched live from OpenAlex

Statement of the Problem: Europe and the whole world have been facing the COVID-19 pandemic. This is a new situation that nobody was prepared or ready to face. Proposed Solution: The reactions to the new situation were solved at different levels from very locally, regionally at the level of member states of EU, international societies and associations and finally coordinated by European Commission (EC), and also with regards the rest of the world, e.g. China, USA, Canada. New COVID-19 biobanks were created as parts of just existing biobanks not well coordinated with each other and harmonized. BBMRI-ERIC (Biobanking and BioMolecular resources Research Infrastructure - European Research Infrastructure Consortium) immediately organized coordinated approach and sharing experience in COVID-19 patient samples and harmonized its activities resulting in joint action sharing COVID-19 databases with ISBER. The European Commission started to coordinate research activities supporting 18 projects with special attendance to following aspects: improving epidemiology and public health, including European preparedness and response to outbreaks. Rapid point-of-care diagnostic tests to reduce the risk of further spread of the virus. New treatments, in which a dual approach: accelerating the development of new treatments and screening and identifying molecules that could work against the virus, using advanced modelling and computing techniques, and development of new vaccines. A COVID-19 data portal was created. COVID-19 industrial cluster response portal was established. SMEs portal involved in COVID-19 was supported. Research infrastructure services to support the fight against COVID- 19 were originated under umbrella of European Commission. The most important activities and actions will be presented. Conclusions: The pandemic has changed all aspects of biobanking life and science, accelerated new techniques and technologies how to collect, process and store COVID-19 samples, basic research, research in the field of new vaccines, therapeutic procedures, implementation of IT solutions. Pandemic supports the international collaboration and samples and data sharing, and creation of new types of virtual biobanks.

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)0.039
metaresearch head score (Gemma)0.042
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: Commentary · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0020.002
Scholarly communication0.0120.011
Open science0.0030.009
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0300.011

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 head0.595
GPT teacher head0.519
Teacher spread0.076 · 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
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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