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Record W2006210376 · doi:10.3109/19401736.2015.1015003

Mitogenome metadata: current trends and proposed standards

2015· article· en· W2006210376 on OpenAlex
Jeff H. T. Strohm, Rodger Gwiazdowski, Robert Hanner

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

VenueMitochondrial DNA Part A · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMetadataCurrent (fluid)BiologyEvolutionary biologyComputational biologyInformation retrievalEcologyComputer scienceBioinformaticsWorld Wide WebOceanographyGeology

Abstract

fetched live from OpenAlex

Mitogenome metadata are descriptive terms about the sequence, and its specimen description that allow both to be digitally discoverable and interoperable. Here, we review a sampling of mitogenome metadata published in the journal Mitochondrial DNA between 2005 and 2014. Specifically, we have focused on a subset of metadata fields that are available for GenBank records, and specified by the Genomics Standards Consortium (GSC) and other biodiversity metadata standards; and we assessed their presence across three main categories: collection, biological and taxonomic information. To do this we reviewed 146 mitogenome manuscripts, and their associated GenBank records, and scored them for 13 metadata fields. We also explored the potential for mitogenome misidentification using their sequence diversity, and taxonomic metadata on the Barcode of Life Datasystems (BOLD). For this, we focused on all Lepidoptera and Perciformes mitogenomes included in the review, along with additional mitogenome sequence data mined from Genbank. Overall, we found that none of 146 mitogenome projects provided all the metadata we looked for; and only 17 projects provided at least one category of metadata across the three main categories. Comparisons using mtDNA sequences from BOLD, suggest that some mitogenomes may be misidentified. Lastly, we appreciate the research potential of mitogenomes announced through this journal; and we conclude with a suggestion of 13 metadata fields, available on GenBank, that if provided in a mitogenomes's GenBank record, would increase their research value.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.547

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 head0.316
Teacher spread0.271 · 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