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Record W2600165649 · doi:10.1071/fp16384

Melatonin in plant signalling and behaviour

2017· article· en· W2600165649 on OpenAlexafffund
Lauren A. E. Erland, Praveen K. Saxena, Susan J. Murch

Bibliographic record

VenueFunctional Plant Biology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMelatoninBiologyNeuroscienceSignallingEcologyCell biology

Abstract

fetched live from OpenAlex

Melatonin is an indoleamine neurotransmitter that has recently become well established as an important multi-functional signalling molecule in plants. These signals have been found to induce several important physiological responses that may be interpreted as behaviours. The diverse processes in which melatonin has been implicated in plants have expanded far beyond the traditional roles for which it has been implicated in mammals, which include sleep, tropisms and reproduction. These functions, however, appear to also be important melatonin mediated processes in plants, though the mechanisms underlying these functions have yet to be fully elucidated. Mediation or redirection of plant physiological processes induced by melatonin can be summarised as a series of behaviours including, among others: herbivore defence, avoidance of undesirable circumstances or attraction to opportune conditions, problem solving and response to environmental stimulus. As the mechanisms of melatonin action are elucidated, its involvement in plant growth, development and behaviour is likely to expand beyond the aspects discussed in this review and hold promise for applications in diverse fundamental and applied plant sciences including conservation, cryopreservation, morphogenesis, industrial agriculture and natural health products.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.222
Teacher spread0.188 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations73
Published2017
Admission routes2
Has abstractyes

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