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Record W6898749330 · doi:10.57912/23878086.v1

Genetic population structure of gray whales (Eschrichtius robustus) that summer in Clayoquot Sound, British Columbia

2023· article· en· W6898749330 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican University Research Archive · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsGray (unit)Population structurePopulationCladeGenetic structuremtDNA control regionMitochondrial DNA

Abstract

fetched live from OpenAlex

To determine the sex composition of gray whales that summer in Clayoquot Sound (CS), British Columbia and to assess whether these animals represent a genetically distinct subgroup of the eastern North Pacific (ENP) population, I collected skin samples from 18 individuals in CS ("residents"). Fourteen samples obtained from other areas served as random representatives of the overall population in the ENP ("non-residents"). Sex was determined for each sample; the nucleotide sequence of a 311 base-pair segment at the 5$\sp\prime$ end of the mtDNA control region was determined by automated sequencing. The sex ratio among residents was 2.6 to 1 nominally biased towards males, but was not significantly different from parity (p = 0.06). Residents were not significantly different from non-residents (Kst = $-$0.02, p = 0.79). Neighbor-joining analysis revealed three clades that did not correspond to any obvious geographic pattern. These data indicate the ENP population is genetically homogeneous.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.265
Teacher spread0.235 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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