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Record W1500717152 · doi:10.1002/0471250953.bi1101s36

An Introduction to the Informatics of “Next‐Generation” Sequencing

2011· review· en· W1500717152 on OpenAlexaff
Lincoln Stein

Bibliographic record

VenueCurrent Protocols in Bioinformatics · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsMassive parallel sequencingDNA sequencingComputer scienceSoftwareInformaticsThroughputData scienceEngineeringBiologyOperating systemGeneticsWirelessDNA

Abstract

fetched live from OpenAlex

Abstract Next‐generation sequencing (NGS) packs the sequencing throughput of a 2000's‐era genome center into a single affordable machine. However, software developed for conventional sequencing technologies is often inadequate to deal with the nature of NGS technologies, which produce short, massively parallel reads. This unit surveys the software packages that are available for managing and analyzing NGS data. Curr. Protoc. Bioinform. 36:11.1.1‐11.1.9. © 2011 by John Wiley & Sons, Inc.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.002
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.010

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 head0.164
GPT teacher head0.380
Teacher spread0.215 · 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
GenreReview

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

Citations19
Published2011
Admission routes1
Has abstractyes

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