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Record W2054090679 · doi:10.1021/jf901618z

DNA Barcoding of Commercially Important Salmon and Trout Species (Oncorhynchus and Salmo) from North America

2009· article· en· W2054090679 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.

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSalmoTroutDNA barcodingFisheryOncorhynchusBiologyRainbow troutSalmonidaeZoologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The present study investigated the ability of DNA barcoding to reliably identify the seven commercially important salmon and trout species (genera Oncorhynchus and Salmo ) in North America. More than 1000 salmonid reference samples were collected from a wide geographic range. DNA extracts from these samples were sequenced for the standard 650 bp barcode region of the cytochrome c oxidase subunit I gene (COI). DNA barcodes showed low intraspecies divergences (mean, 0.26%; range, 0.04-1.09%), and the mean congeneric divergence was 32-fold greater, at 8.22% (range, 3.42-12.67%). The minimum interspecies divergence was always greater than the maximum intraspecies divergence, indicating that these species can be reliably differentiated using DNA barcodes. Furthermore, several shorter barcode regions (109-218 bp), termed "mini-barcodes", were identified in silico that can differentiate all eight species, providing a potential means for species identification in heavily processed products.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.331

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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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