MétaCan
Menu
Back to cohort
Record W1631958718

Infrafrontier - Mouse models and phenotyping data for the European biomedical research community

2009· article· en· W1631958718 on OpenAlexaboutno aff
Michael Raess, Martin Hrabě de Angelis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene Regulatory Network Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCzechPolitical scienceEuropean communityEuropean Research AreaLibrary scienceEuropean unionRegional sciencePublic administrationBusinessGeographyComputer scienceInternational trade
DOInot available

Abstract

fetched live from OpenAlex

It is clear that this tremendous task cannot be fulfilled by individual research facilities or on the national level alone. This is the rationale for the European project Infrafrontier (The European infrastructure for phenotyping and archiving of model mammalian genomes, www.infrafrontier.eu ), which is coordinated at the Helmholtz Zentrum Munchen by Prof. Hrabe de Angelis. Infrafrontier is on the European roadmap for research infrastructures of ESFRI (European Strategy Forum for Research Infrastructures, http://www.cordis.europa.eu/esfri ) and receives funding from the EC’s Seventh Framework Program. It will organise a pan-European research infrastructure to increase the capacities for systemic phenotyping and archiving of mouse models. The Infrafrontier consortium currently contains 22 partners (representing 14 phenotyping and archiving centres, 1 bioinformatics institute and 12 European ministries and funding agencies) from 10 different European countries. Six new partners will join Infrafrontier in the near future, extending the project to Austria, Czech Republic and Canada.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.001
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 head0.119
GPT teacher head0.353
Teacher spread0.234 · 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 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicGene Regulatory Network AnalysisFrench-language works237,207