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<scp>fingerprint</scp>: visual depiction of variation in multiple sequence alignments

2007· article· en· W2092328126 on OpenAlexafffund
Melanie Lou, G. Brian Golding

Bibliographic record

VenueMolecular Ecology Notes · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsMcMaster University
FundersOntario Genomics InstituteGenome Canada
KeywordsFingerprint (computing)Set (abstract data type)VisualizationSequence (biology)Computer scienceFeature (linguistics)Computational biologyBiologyFocus (optics)Artificial intelligenceGeneticsProgramming language

Abstract

fetched live from OpenAlex

Abstract There is a lack of programs available that focus on providing an overview of an aligned set of sequences such that the comparison of homologous sites becomes comprehensible and intuitive. Being able to identify similarities, differences, and patterns within a multiple sequence alignment is biologically valuable because it permits visualization of the distribution of a particular feature and inferences about the structure, function, and evolution of the sequences in question. We have therefore created a web server, fingerprint, which combines the characteristics of existing programs that represent identity, variability, charge, hydrophobicity, solvent accessibility, and structure along with new visualizations based on composition, heterogeneity, heterozygosity, d N / d S and nucleotide diversity. fingerprint is easy to use and globally accessible through any computer using any major browser. fingerprint is available at http://evol.mcmaster.ca/fingerprint/ .

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.118
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1180.016

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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

Citations19
Published2007
Admission routes2
Has abstractyes

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