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Record W1995923160 · doi:10.1139/b04-118

Thermogenic flowering of taro (<i>Colocasia esculenta</i>, Araceae)

2004· article· en· W1995923160 on OpenAlexvenueno aff
Anton Ivančič, Vincent Lebot, Olivier Roupsard, José Quero García, T. Okpul

Bibliographic record

VenueCanadian Journal of Botany · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAraceaeColocasia esculentaInflorescencePollinationPollenBiologyBotanyHorticultureMorning

Abstract

fetched live from OpenAlex

Thermogenesis and its association with taro (Colocasia esculenta (L.) Schott) flowering was studied during the warmest period of the year (December 2002 – February 2003) within a large collection of heterogeneous plant material on Espiritu Santo, Vanuatu. On each studied inflorescence, temperatures of the three main parts of the spadix and the ambient air were recorded during a period of 38 h. The investigation indicates that significant thermogenic activity of taro inflorescences takes place during two successive nights: (1) during the night when an inflorescence becomes odorous (the female phase) and (2) a night later, when microsporogenesis approaches its final phase (the male phase). The highest average difference between mean temperatures of the ambient air and inflorescences were documented during the female phase, at 0500 hours (the mean temperature of the sterile appendix was 29.1 ± 0.9 °C (P = 0.05) and this was 6.8 °C above the temperature of the ambient air). Thermogenic activity is synchronized with the protogynous nature of the species and insect pollination in the early morning hours. Its main putative functions are (1) to reduce the deviations of ambient air temperatures during the most critical periods of flowering, and (2) to promote cross-pollination. It stops 1–1.5 h after pollen has been released.Key words: taro, Colocasia esculenta, thermogenesis, inflorescence development, pollination.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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 designQualitative
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

Citations27
Published2004
Admission routes1
Has abstractyes

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