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Record W3206709215 · doi:10.3390/taxonomy1040023

Cytogeography of the Solidago rugosa Mill. Complex (Asteraceae: Astereae) in Eastern North America

2021· article· en· W3206709215 on OpenAlexafffund
John C. Semple, Jie Zhang, Rachel E. Cook, Bambang Agus Suripto

Bibliographic record

VenueTaxonomy · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRugosaAsteraceaeRange (aeronautics)BotanyBiologyChromosome numberGeographyChromosomeKaryotype

Abstract

fetched live from OpenAlex

Chromosome numbers are reported here for the first time from 117 individuals of Solidago rugosa and S. fistulosa. Including 178 previously published reports for the two species plus S. latissimifolia, chromosome numbers have been determined from 295 individuals from 269 locations. Only diploids (2n = 18) were found throughout the range of S. fistulosa on the coastal plain in the eastern U.S.A. (44 counts). Diploids (2n = 18) were found in the northern portion of the range of S. latissimifolia, and tetraploids (2n = 36) and hexaploids (2n = 54) were found in the central and southern portions of the range (nine counts in total). Diploids (2n = 18) were found throughout the range of S. rugosa in much of eastern North America in four of the five varieties (northern var. rugosa, var. sphagnophila; southern var. aspera and var. celtidifolia). Tetraploids (2n = 36) were found in all four of these varieties and exclusively in var. cronquistiana in the southern high Appalachian Mountains. Hexaploids (2n = 54) were found in var. sphagnophila at scattered locations. One possible hexaploid in var. rugosa was found in the Allegheny Mountains. The diversity in ploidy levels was independent of the size of the range and the diversity of growing conditions among the three species of S. subsect. Venosae.

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 score0.280
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.218
Teacher spread0.178 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

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