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Record W2076900008 · doi:10.1116/1.2188519

Breaking bonds in the atomic force microscope: Extracting information

2006· article· en· W2076900008 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

VenueBiointerphases · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaKillam TrustsDalhousie University
KeywordsForce spectroscopyCantileverAtomic force microscopyForce constantConstant (computer programming)Kelvin probe force microscopeChemistryFunction (biology)Bond lengthPolymerElectrostatic force microscopeNanotechnologyMolecular physicsComputational chemistryMaterials scienceMoleculeComposite materialComputer scienceOrganic chemistry

Abstract

fetched live from OpenAlex

A theoretical framework is developed to analyze molecular bond breaking in dynamic force spectroscopy using atomic force microscopy (AFM). An analytic expression of the observed bond breaking probability as a function of force is obtained in terms of the relevant physical parameters. Three different experimental realizations are discussed, in which (i) the force is increased linearly in time, and (ii) the AFM cantilever is moved at constant speed, and (iii) the force is held constant. We find that unique fitting of the bond parameters such as the potential depth and its width is possible only when data from rather different force-loading rates is used. The complications in the analysis of using the constant velocity mode arising from the intermediate polymer spacer are discussed at length.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.297

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 head0.005
GPT teacher head0.264
Teacher spread0.259 · 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