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Record W4312080161 · doi:10.1139/cjb-2022-0073

Macro- and micromorphology reveal four entities in the highly variable <i>Oxalis polymorpha</i> Mart. ex Zucc. (Oxalidaceae)

2022· article· en· W4312080161 on OpenAlexvenueno aff
Everton Richetti, Duane Fernandes Lima, Pedro Fiaschi, Makeli Garibotti Lusa

Bibliographic record

VenueBotany · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyBotanyIndumentumDisjunctInflorescenceTaxonTaxonomy (biology)Phylogenetic treePedicelPetalDisjunct distributionPopulation

Abstract

fetched live from OpenAlex

Leaf morphoanatomy can provide useful information for the taxonomy of morphologically similar species or the recognition of infraspecific taxa. Here, we evaluated the taxonomic utility of leaf morphological and anatomical characters for the recognition of distinct morphologies currently placed under Oxalis polymorpha Mart. ex Zucc., a highly polymorphic species of Oxalis from the Brazilian Atlantic Forest. We analyzed leaves of 13 specimens gathered from five populations throughout the species' geographic distribution. Leaf samples were analyzed under light and scanning electron microscopy. We observed differences in the leaf blade venation patterns, in the indumentum of petioles and leaf blades, in the pulvinar vascular tissue configuration, and in the midrib tissue organization. The variation in these characters allowed us to recognize four different morphotypes among these samples. These morphotypes are geographically disjunct and differ among each other in additional morphological features, such as leaf arrangement along the stem, leaflet shape, inflorescence position, petal color, and fruit shape. Oxalis polymorpha is a good candidate for investigating if phylogenetic relationships support recognition of each of its morphotypes at the species level.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.742

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 studies0.0000.000
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 head0.016
GPT teacher head0.173
Teacher spread0.157 · 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 designBench or experimental
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

Citations7
Published2022
Admission routes1
Has abstractyes

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