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Record W2096246501 · doi:10.1155/2007/743101

Ultra‐spatial synchrotron radiation for imaging molecular chemical structure: Applications in plant and animal studies

2007· article· en· W2096246501 on OpenAlexafffund
Peiqiang Yu

Bibliographic record

VenueJournal of Spectroscopy · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsUniversity of Saskatchewan
FundersBrookhaven National LaboratoryNatural Sciences and Engineering Research Council of CanadaCenters for Disease Control and PreventionDivision of Materials ResearchU.S. Department of EnergyNational Science Foundation
KeywordsSynchrotronSynchrotron radiationBrightnessInfraredFourier transform infrared spectroscopyFourier transformChemistryChemical imagingMaterials scienceNanotechnologyBiological systemOpticsComputer sciencePhysicsHyperspectral imagingBiology

Abstract

fetched live from OpenAlex

Synchrotron‐based Fourier transform infrared microspectroscopy (S‐FTIR) has been developed as a rapid, direct, non‐destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical features and make‐up within microstructures of a biological tissue without destruction of inherent structures at ultra‐spatial resolutions within cellular dimension. To date there has been very little application of this advanced synchrotron technique to the study of plant and animal tissues′ inherent structure at a cellular or subcellular level. In this article, a novel approach was introduced to show the potential of the newly developed, advanced synchrotron‐based analytical technology, which can be used to reveal molecular structural‐chemical features of various plant and animal tissues.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.341
Teacher spread0.334 · 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 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

Citations5
Published2007
Admission routes2
Has abstractyes

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