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Record W4295780688 · doi:10.21203/rs.3.rs-1717433/v1

Autofluorescence-decrease phenomenon of woody cell in Lophira alata

2022· preprint· en· W4295780688 on OpenAlexaff
Zhaoyang Yu, Dongnian Xu, Jinbo Hu, Shanshan Chang, Gonggang Liu, Qiongtao Huang, Han Jin, Ting Li, Yuan Liu, Xiaodong Wang

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsUniversité Laval
FundersNatural Science Foundation of Hunan ProvinceNational Natural Science Foundation of China
KeywordsAutofluorescencePhenomenonOpticsPhysicsFluorescence

Abstract

fetched live from OpenAlex

Abstract Background: Fluorescence is an intrinsic property of lignin. However, the autofluorescence of Lophira alata ( L. alata ) was found to be almost invisible during an occasional fluorescence observation experiment. The purpose of this study was to investigate the reason why lignin autofluorescence is invisible in L. alata . Results : Herein, the autofluorescence microscopy, diffuse reflection spectra and UV-Vis absorption spectra of L. alata have been performed. In order to recognize the relationship between autofluorescence phenomenon and anatomical structure, themacroscopic, microscopic and ultramicroscopic characteristics of L. alata are also examined. Results show that both the longitudinal parenchyma and the rays are rich in extractives. Moreover, these extractives have infiltrated into the vessels and fibers. The autofluorescence of the wood becomes increasingly clear after the benzene–alcohol extraction treatment. Meanwhile, UV-Vis absorption spectrashow that the extractives from L. alata have a strong absorption to light at a wavelength range of 200-500 nm. Conclusions : The complex compounds like polyphenols or terpenoids contained in the rich extractives of L. alata are likely to affect the autofluorescence of lignin.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0000.001
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 head0.039
GPT teacher head0.367
Teacher spread0.328 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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