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Record W4398239106 · doi:10.1139/facets-2023-0099

Heliocaminiform structures: plant organs that function as microgreenhouses

2024· article· en· W4398239106 on OpenAlexaffvenue
Peter G. Kevan, Charlotte Coates

Bibliographic record

VenueFACETS · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFunction (biology)BiologyEvolutionary biology

Abstract

fetched live from OpenAlex

Plant structures that enclose trapped air are morphologically and taxonomically diverse. They range from pubescence (trichomes) on various parts of plants to flowers, inflorescences, stems, culms (above-ground jointed stems of grasses), petioles, peduncles, scapes, fruits, bracts, leaves, galls, algal pneumatocysts, moss sporophytes, lichen podetia, and fungal fruiting bodies. Despite being familiar, such structures have not been studied systematically until recently when their complex thermodynamic functionality as microgreenhouses has been recognized. We propose the term “heliocaminiform” (Greco-Latin origin for “sun-room”) provides an umbrella term that describes form and function. Almost all the hollow structures we have examined have elevated internal temperatures of several degrees C above the surrounding air in sunshine, but those are abolished under cloud or at night. The potential importance for the additional heat is presumed to be in growth, maturation, reproduction, sexual function, and overall fitness of the plants. There seem to be no experimental studies on those effects even though they may help explain aspects of plants’ responses to climate change and to phenological mismatches with symbionts (mutualists and herbivores) as ecologically co-dependent partners. Our review and observations opens a remarkably new and hitherto surprisingly neglected avenue in botany which we hope others will explore.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.999

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)0.0010.002

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 head0.209
Teacher spread0.193 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2024
Admission routes2
Has abstractyes

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