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Nanometrology of delignified<i>Populus</i>using mode synthesizing atomic force microscopy

2011· article· en· W2157706012 on OpenAlexaff
Laurène Tétard, Ali Passian, R. H. Farahi, Brian H. Davison, Sung‐Jin Jung, Arthur J. Ragauskas, Aude L. Lereu, Thomas Thundat

Bibliographic record

VenueNanotechnology · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersNational Renewable Energy Laboratory
KeywordsNanometrologyMaterials scienceAtomic force microscopyNanoscopic scaleNanotechnologyMetrologyMicroscopyOpticsPhysics

Abstract

fetched live from OpenAlex

The study of the spatially resolved physical and compositional properties of materials at the nanoscale is increasingly challenging due to the level of complexity of biological specimens such as those of interest in bioenergy production. Mode synthesizing atomic force microscopy (MSAFM) has emerged as a promising metrology tool for such studies. It is shown that, by tuning the mechanical excitation of the probe-sample system, MSAFM can be used to dynamically investigate the multifaceted complexity of plant cells. The results are argued to be of importance both for the characteristics of the invoked synthesized modes and for accessing new features of the samples. As a specific system to investigate, we present images of Populus, before and after a holopulping treatment, a crucial step in the biomass delignification process.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.288
Teacher spread0.266 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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