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Record W4307777294 · doi:10.1039/d2nr04823j

Autofluorescence spectroscopy for quantitative analysis of cellulose nanocrystals

2022· article· en· W4307777294 on OpenAlexafffund
Marcus A. Johns, Jude Abu-Namous, Hongying Zhao, M. Gattrell, James Lockhart, Emily D. Cranston

Bibliographic record

VenueNanoscale · 2022
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsBC Research (Canada)University of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMitacsE.W.R. Steacie Memorial Fund
KeywordsAutofluorescenceCelluloseSpectroscopyNanocrystalMaterials scienceQuantitative analysis (chemistry)NanotechnologyAnalytical Chemistry (journal)ChemistryOpticsChromatographyFluorescenceOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

CNC for the surface charge content. This charge-coupled device (CCD) sensor-based methodology is rapid and does not require the addition of further chemicals. These results support the theory behind CTE and represent a new opportunity for quantitatively analysing non-aromatic, heteroatom-containing nanoparticles in flow based on understanding their inter- and intra-particle interactions.

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 categoriesInsufficient 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 score0.007
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.331
Teacher spread0.302 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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