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Record W4313678558 · doi:10.1038/s41598-022-27108-8

How the volatile organic compounds emitted by corpse plant change through flowering

2023· article· en· W4313678558 on OpenAlexaff
Lili Kang, Jasmeen Kaur, Kelsey Winkeler, Daniella Kubiak, Jane E. Hill

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOdorPeriod (music)Mass spectrometryHorticultureGas chromatography–mass spectrometryBotanyBiologyChemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

The corpse plant (Amorphophallus titanum) is so named because it produces a pungent, foul odor when flowering. Little is known about how the emitted volatiles change throughout the two-day flowering period. In this study, the comprehensive monitoring of the presence and change in volatile molecules during the female and the male flowering phases of A. titanum was conducted, and the plant temperature was monitored. A total of 422 volatile features were detected over the entire sampling period, of which 118 features were statistically significantly different between the pre-flowering and both flowering phases, and an additional 304 features were found present throughout the flowering period. A total of 45 molecules could be assigned putative names. The volatile profile of A. titanum changes over the two-day flowering period, with the S-containing molecules and aldehydes dominant in the female flowering phase, and the alcohols and hydrocarbons dominant in the male flowering phase. The two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) enabled us to identify 32 new molecules produced by A. titanum. Each of these molecules alone, and in combination, likely contribute to the different odors emitted during the flowering phase of A. titanum.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.038
GPT teacher head0.214
Teacher spread0.175 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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