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Record W2114352223 · doi:10.2980/19-2-3452

Distyly, floral visitors, and fructification in 2 natural populations of <i>Psychotria nervosa</i> (Rubiaceae)

2012· article· en· W2114352223 on OpenAlexvenueno aff
Angélica María Hernández-Ramírez

Bibliographic record

VenueEcoscience · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersSistema Nacional de InvestigadoresConsejo Nacional de Ciencia y Tecnología
KeywordsPsychotriaBiologyRubiaceaeHeterostylyPopulationInflorescenceDioecyFructificationBotanyEcologyPollinationPollenDemography

Abstract

fetched live from OpenAlex

Distyly is a common reproductive strategy in the family Rubiaceae. Studies on tropical species of the genus Psychotria present several cases of atypical distyly, e.g., the absence of reciprocal positioning of sexual organs between morphs, anisoplethy, limited pollen availability, and monomorphy. To describe the floral polymorphism and reproductive ecology of Psychotria nervosa, I studied the proportion of morphs, the floral morphology, the number of inflorescences, flowers, and fruits set between morphs, and the diversity and behaviour of floral visitors in 2 natural populations of the species in a seasonally dry tropical forest in Mexico. Psychotria nervosa is a distylous species; both populations presented a 1:1 morph ratio, with reciprocal positioning of sexual organs between morphs, as well as a suite of ancillary floral traits associated to polymorphism. The diversity and behaviour of the floral visitor assemblage caused a higher fruit set in the long-styled morph than in the short-styled morph in both populations. Furthermore, the highest fruit set was observed in the most morphologically reciprocal population.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.050
GPT teacher head0.245
Teacher spread0.194 · 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

Citations9
Published2012
Admission routes1
Has abstractyes

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