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Record W2530748177 · doi:10.1093/bioinformatics/btw634

ARResT/Interrogate: an interactive immunoprofiler for IG/TR NGS data

2016· article· en· W2530748177 on OpenAlexfundno aff
Vojtěch Bystrý, Tomáš Reigl, Adam Krejčí, Martin Demko, Barbora Hanáková, Andrea Grioni, Henrik Knecht, Max Schlitt, Peter Dreger, Leopold Sellner, Dietrich Herrmann, Pingeon Marine, Myriam Boudjoghra, Jos Rijntjes, Christiane Pott, Anton W. Langerak, Patricia J.T.A. Groenen, Frédéric Davi, Monika Brüggemann, Nikos Darzentas

Bibliographic record

VenueBioinformatics · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsnot available
FundersOVC Pet TrustMinisterstvo Školství, Mládeže a TělovýchovyCentral European Institute of TechnologyUniversity of Guelph
KeywordsComputer scienceTask (project management)Filter (signal processing)Interpretation (philosophy)Web applicationData scienceComputational biologyWorld Wide WebBiologyProgramming language

Abstract

fetched live from OpenAlex

Motivation: The study of immunoglobulins and T cell receptors using next-generation sequencing has finally allowed exploring immune repertoires and responses in their immense variability and complexity. Unsurprisingly, their analysis and interpretation is a highly convoluted task. Results: We thus implemented ARResT/Interrogate, a web-based, interactive application. It can organize and filter large amounts of immunogenetic data by numerous criteria, calculate several relevant statistics, and present results in the form of multiple interconnected visualizations. Availability and Implementation: ARResT/Interrogate is implemented primarily in R, and is freely available at http://bat.infspire.org/arrest/interrogate/ Contact: nikos.darzentas@gmail.com Supplementary Information: Supplementary data are available at Bioinformatics online.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.580
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.032
GPT teacher head0.276
Teacher spread0.244 · 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 designBench or experimental
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

Citations106
Published2016
Admission routes1
Has abstractyes

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