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Record W2009556043 · doi:10.1063/1.2177542

Calibrating laser beam deflection systems for use in atomic force microscopes and cantilever sensors

2006· article· en· W2009556043 on OpenAlexaff
Luc Beaulieu, Michel Godin, Olivier Laroche, Vincent Tabard‐Cossa, Peter Grütter

Bibliographic record

VenueApplied Physics Letters · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMcGill UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsCantileverDeflection (physics)OpticsPhotodetectorLaserLaser beamsMicroscopeAtomic force microscopyMaterials scienceLaser beam qualityPhysicsNanotechnology

Abstract

fetched live from OpenAlex

Most atomic force microscopes and cantilever-based sensors use an optical laser beam detection system to monitor cantilever deflections. We have developed a working model that accurately describes the way in which a position sensitive photodetector interprets the deflection of a cantilever in these instruments. This model exactly predicts the numerical relationship between the measured photodetector signal and the actual cantilever deflection. In addition, the model is used to optimize the geometry of such laser deflection systems, which greatly simplifies the use of any cantilever-based instrument that uses a laser beam detection system.

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)0.006
metaresearch head score (Gemma)0.014
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 score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.009
GPT teacher head0.232
Teacher spread0.224 · 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

Citations36
Published2006
Admission routes1
Has abstractyes

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