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Record W2163504106 · doi:10.1039/c4cp04427d

Atomic force microscopy in biomaterials surface science

2014· article· en· W2163504106 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Ottawa
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaUniversità degli Studi di TriesteCanada Foundation for InnovationInstitut national de la recherche scientifiqueUniversity of Ottawa
KeywordsAtomic force microscopyNanotechnologyToolboxMaterials scienceMicroscopyChemistryPhysicsEngineeringOpticsMechanical engineering

Abstract

fetched live from OpenAlex

Recent progress in surface science, nanotechnology and biophysics has cast new light on the correlation between the physicochemical properties of biomaterials and the resulting biological response. One experimental tool that promises to generate an increasingly more sophisticated knowledge of how proteins, cells and bacteria interact with nanostructured surfaces is the atomic force microscope (AFM). This unique instrument permits to close in on interfacial events at the scale at which they occur, the nanoscale. This perspective covers recent developments in the exploitation of the AFM, and suggests insights on future opportunities that can arise from the exploitation of this powerful technique.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.282
Teacher spread0.276 · 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