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Record W2121621283 · doi:10.1093/bioinformatics/btg004

IslandPath: aiding detection of genomic islands in prokaryotes

2003· article· en· W2121621283 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioinformatics · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsBC Cancer AgencySimon Fraser University
Fundersnot available
KeywordsComputational biologyComputer scienceBiology

Abstract

fetched live from OpenAlex

UNLABELLED: Genomic islands (clusters of genes of potential horizontal origin in a prokaryotic genome) are frequently associated with a particular adaptation of a microbe that is of medical, agricultural or environmental importance, such as antibiotic resistance, pathogen virulence, or metal resistance. While many sequence features associated with such islands have been adopted separately in applications for analysis of genomic islands, including pathogenicity islands, there is no single application that integrates multiple features for island detection. IslandPath is a network service which incorporates multiple DNA signals and genome annotation features into a graphical display of a bacterial or archaeal genome, to aid the detection of genomic islands. AVAILABILITY: This application is available at http://www.pathogenomics.sfu.ca/islandpath and the source code is freely available, under GNU public licence, from the authors. SUPPLEMENTARY INFORMATION: An online help file, which includes analyses of the utility of IslandPath, can be found at http://www.pathogenomics.sfu.ca/islandpath/current/islandhelp.html

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.116

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 communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.216
Teacher spread0.193 · 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