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Mitochondrial DNA diversity in North American and European Atlantic salmon with emphasis on the Downeast rivers of Maine

2000· article· en· W2046370834 on OpenAlexaboutno aff
Tim L. King, Adrian P. Spidle, Michael S. Eackles, Barbara A. Lubinski, William B. Schill

Bibliographic record

VenueJournal of Fish Biology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHaplotypeBiologyMitochondrial DNAMonophylyPopulationZoologyEcologyGeneticsPhylogeneticsGeneCladeDemographyAllele

Abstract

fetched live from OpenAlex

The displacement loop and NADH‐1 dehydrogenase regions of mitochondrial DNA (mtDNA) were amplified by the polymerase chain reaction in 954 Atlantic salmon and digested with 40 restriction endonucleases. Variation was detected with 10 enzymes, resulting in 21 composite haplotypes which were strongly patterned geographically with a major discontinuity observed between most North American (NA) and European salmon. Significant heterogeneity of haplotype frequencies was found within and among all classification levels (continent, country, and river). Haplotype frequencies were significantly different across continents, within European samples, within NA samples, within Canadian samples, within wild Maine samples, within captive Maine strains, and between captive and wild Maine strains. Nine haplotypes occurred only in NA, seven in Maine, three only in Maine, and 11 occurred only in Europe. Some Maine rivers had only a single haplotype, suggesting that effective population sizes may be low. The second most frequent European haplotype occurred in tributaries to one Newfoundland river. Gene trees based on parsimony and genetic distance suggest that the haplotypes are monophyletic within each continent, and that the haplotype found on both continents is intermediate between those of Europe and NA, suggesting common ancestry of all haplotypes.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.384

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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations50
Published2000
Admission routes1
Has abstractyes

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