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Record W2007767180 · doi:10.2144/05385st01

Management and Visualization of Whole Genome Shotgun Assemblies Using SAM

2005· article· en· W2007767180 on OpenAlexafffund
Robin M. Warren, Yaron S.N. Butterfield, Ryan D. Morin, Asim Siddiqui, Marco A. Marra, Steven J.M. Jones

Bibliographic record

VenueBioTechniques · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsGenome British Columbia
FundersMichael Smith Health Research BCGenome British ColumbiaCanada's Michael Smith Genome Sciences CentreGenome Canada
KeywordsPerlGenomeShotgun sequencingSequence assemblyVisualizationComputational biologyComputer scienceInterface (matter)Sequence (biology)Whole genome sequencingShotgunBiologyDatabaseProgramming languageGeneticsData miningOperating systemGene

Abstract

fetched live from OpenAlex

We have designed and implemented a system to manage whole genome shotgun sequences and whole genome sequence assembly data flow. The Sequence Assembly Manager (SAM) consists primarily of a MySQL relational database and Perl applications designed to easily manipulate and coordinate the analysis of sequence information and to view and report genome assembly progress through its Common Gateway Interface (CGI) web interface. The application includes a tool to compare sequence assemblies to fingerprint maps that has been used successfully to improve and validate both maps and sequence assemblies of the Rhodococcus sp.RHAI and Cryptococcus neoformans WM276 genomes.

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: Software · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.005

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 head0.017
GPT teacher head0.282
Teacher spread0.265 · 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
GenreSoftware

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

Citations8
Published2005
Admission routes2
Has abstractyes

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