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Referee report. For: StackbarExtended: a user-friendly stacked bar-plot representation incorporating phylogenetic information and microbiota differential abundance analysis [version 1; peer review: 1 approved]

2024· article· en· W4416639836 on OpenAlexfundno aff
Zheng Sun

Bibliographic record

VenueFaculty of 1000 Research Ltd · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversité de MontréalMcMaster University
KeywordsPhylogenetic treeRepresentation (politics)Abundance (ecology)Feature (linguistics)PhylogeneticsPattern recognition (psychology)

Abstract

fetched live from OpenAlex

Background Microbial communities are mainly composed of bacteria, archaea, viruses and fungi, and are present in the gut, mouth, nose, skin, lungs, vagina, and bladder, among other places. In recent years, research has highlighted the critical role that these highly complex communities play in health and disease. Advances in sequencing technology have resulted in the development of high-dimensional data, which are challenging to effectively analyze and visualize. In this context, traditional stacked bar-plot visualizations, while widely used, fall short of conveying the fundamental phylogenic relationships between community members and are thus difficult to interpret. Methods StackbarExtended is implemented in native R, required version (≥ 4.0), and is platform independent, with its source code available on GitHub and archived on Zenodo. Results StackbarExtended allows for the plotting of relative abundance at user-defined taxonomic levels while displaying phylogenetic information using color gradients. Additionally, StackbarExtended integrates differential abundance statistics directly into the visualization process and performs clustering of low-abundance taxa. Conclusions StackbarExtended offers researchers a user-friendly tool for rapid visualization, presentation, and analysis of the microbiota composition.

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)0.007
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.090
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.006
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0040.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.8430.573

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 head0.032
GPT teacher head0.373
Teacher spread0.342 · 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.

Study designNot applicable
DomainEvaluation
GenreCommentary

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".

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Citations0
Published2024
Admission routes1
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