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A distortion-free single-chip atomic force microscope with 2DOF isothermal scanning

2015· article· en· W1563691014 on OpenAlexafffund
D. Strathearn, G. Lee, Niladri Sarkar, M. Olfat, Raafat R. Mansour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Waterloo
FundersDefense Advanced Research Projects AgencyCMC Microsystems
KeywordsDistortion (music)ScannerChipMaterials scienceMicroscopeOpticsScanning probe microscopyNon-contact atomic force microscopyScanning Hall probe microscopeResolution (logic)Coupling (piping)ActuatorAtomic force microscopyOptoelectronicsScanning electron microscopeConductive atomic force microscopyNanotechnologyComputer sciencePhysicsArtificial intelligenceConventional transmission electron microscope

Abstract

fetched live from OpenAlex

A distortion free single-chip scanning probe microscope (sc-SPM) has been developed. The reported design integrates the 3 DOF scanner, sensors, and tip that are required for nanometer-scale measurements onto a single chip. This low-cost instrument has achieved imaging resolution comparable to conventional tools without the image distortion that was present in prior single-chip SPMs, arising from thermal coupling between electrothermal actuators. A single chip atomic force microscope is used with a novel 2D isothermal scanning algorithm to obtain a 5 μm × 3 μm rectangular topographical map, free from image distortion.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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
GenreMethods

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
Published2015
Admission routes2
Has abstractyes

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