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Record W2169887621 · doi:10.3109/19401730903168182

Testing taxonomic boundaries and the limit of DNA barcoding in the Siberian sturgeon,<i>Acipenser baerii</i>

2009· article· en· W2169887621 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

VenueMitochondrial DNA · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Guelph
FundersGenome Canada
KeywordsSubspeciesDNA barcodingSturgeonBiologyMitochondrial DNAZoologyCytochrome c oxidase subunit IEcologyEvolutionary biologyFisheryGeneGeneticsFish <Actinopterygii>

Abstract

fetched live from OpenAlex

DNA barcoding efforts involving animals have focused on the mitochondrial cytochrome c oxidase subunit I (Cox1) gene. Some authors suggest that this marker might under-diagnose young species. Herein, we examine Cox1 and control region diversity in a sample of Siberian sturgeon (Acipenser baerii), a species with an extremely wide geographic distribution in the major rivers of Siberia and in Lake Baikal. Some authors currently recognize three subspecies within this species. These subspecies are reasonable candidates for species units detectable through DNA barcoding. The Cox1 gene illustrated no variation within the species, while the control region displayed statistically significant differences among the subspecies using analysis of molecular variance (AMOVA). Given the uniformity of Cox1 sequences recovered, Cox1 is probably a good region for barcoding A. baerii at the species level. Although control region variation among subspecies was significant, diagnostic differences were not found for any of the subspecies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.375

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 studies0.0000.001
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 head0.014
GPT teacher head0.208
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