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Record W2172168366 · doi:10.1111/jpy.12237

Long distance kelp rafting impacts seaweed biogeography in the Northeast Pacific: the kelp conveyor hypothesis

2014· letter· en· W2172168366 on OpenAlexafffund
Gary W. Saunders

Bibliographic record

VenueJournal of Phycology · 2014
Typeletter
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaNew Brunswick Innovation FoundationOntario Genomics Institute
KeywordsKelpBiologyKelp forestHoldfastDNA barcodingEcologyRange (aeronautics)LaminariaAlgaeThallusBotany

Abstract

fetched live from OpenAlex

Routine DNA barcoding of the Haida Gwaii seaweed flora revealed "endemic species" attributed initially to this region's past as a glacial refugium. However, subsequent barcode records from central California rapidly eroded this list leaving species characterized by disjunct distributions (DD) between California and Haida Gwaii. This observation prompted a more detailed look at species for California and British Columbia and revealed that 33 of 180 DNA-barcoded genetic groups in common between these regions (~18%) predominantly displayed DD between California and northern British Columbia. A previous discovery that a red abalone shell found in Haida Gwaii (far north of its range) had a float-bearing kelp (Nereocystis luetkeana) holdfast attached to it prompted a closer consideration of the COI-5P barcode data in support of a "kelp conveyor hypothesis." The hypothesis posits that there has been a net migration of Californian species to northern British Columbia the vector being species growing on substrata carried along with kelp rafts on the winter Davidson Current.

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)0.002
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0150.012
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.201
Teacher spread0.185 · 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

Citations47
Published2014
Admission routes2
Has abstractyes

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