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Record W2145051467 · doi:10.1071/bt03101

Morphology and spatial distribution of alien sea-rockets ( <i>Cakile</i> spp.) on South Australian and Western Canadian beaches

2004· article· en· W2145051467 on OpenAlexaboutno aff
Timothy W. D. Cody, Martin L. Cody

Bibliographic record

VenueAustralian Journal of Botany · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyIntrogressionEcologyTaxonPhylogeographyRange (aeronautics)Biological dispersalBiogeographyGeographyPhylogeneticsPopulation

Abstract

fetched live from OpenAlex

Sea-rockets ( Cakile spp., Brassicaceae) are annual plants of sandy beaches. Cakile edentula (Bigel.) Hook. is native to the eastern coast of North America, C. maritima Scop. to western Europe and the Mediterranean basin. The two species differ in several morphological features, including leaf form, fruits and petal size. Both are long-established aliens on beaches in western Canada and southern Australia, at sites where we examined their morphological and distributional attributes. The two Cakile species co-occur at Pachina Beach, British Columbia, Canada, with C. edentula more common and widely distributed over broader range of beach elevations and C. maritima restricted to the upper beach. Although a few putative hybrids occur, the species are morphologically quite distinct. In contrast, on Westlake Shores beach, South Australia, Cakile is at least in part perennial, with widely variable morphologies, and the taxon is not separable into two morphologically distinct entities. Species boundaries have blurred apparently because of introgression. Factors that may have lead to this contrasting situation in South Australia are discussed.

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)0.000
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 score0.239
Threshold uncertainty score0.480

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.214
Teacher spread0.196 · 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

Citations18
Published2004
Admission routes1
Has abstractyes

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