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Record W2621457453 · doi:10.1093/bioinformatics/btx367

MoDMaps3D: an interactive webtool for the quantification and 3D visualization of interrelationships in a dataset of DNA sequences

2017· article· en· W2621457453 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioinformatics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFractal and DNA sequence analysis
Canadian institutionsUniversity of WaterlooWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVisualizationComputer scienceComputational biologyDNAInteractive visualizationComputer graphics (images)Artificial intelligenceData miningBiologyGenetics

Abstract

fetched live from OpenAlex

SUMMARY: MoDMaps3D (Molecular Distance Maps 3D) is an alignment-free, fast, computationally lightweight webtool for computing and visualizing the interrelationships within any dataset of DNA sequences, based on pairwise comparisons between their oligomer compositions. MoDMaps3D is a general-purpose interactive webtool that is free of any requirements on sequence composition, position of the sequences in their respective genomes, presence or absence of similarity or homology, sequence length, or even sequence origin (biological or computer-generated). AVAILABILITY AND IMPLEMENTATION: MoDMaps3D is open source, cross-platform compatible, and is available under the MIT license at http://moleculardistancemaps.github.io/MoDMaps3D/. The source code is available at https://github.com/moleculardistancemaps/MoDMaps3D/. CONTACT: lila@uwaterloo.ca. 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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.148

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 head0.045
GPT teacher head0.344
Teacher spread0.299 · 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