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Record W2060283768 · doi:10.1063/1.4802678

A high-speed magnetic tweezer beyond 10,000 frames per second

2013· article· en· W2060283768 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of Scientific Instruments · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of California, Santa BarbaraNational Science Foundation
KeywordsMagnetic tweezersBiomoleculeTracking (education)Optical tweezersSpeed of light (cellular automaton)OpticsPhysicsMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

The magnetic tweezer is a single-molecule instrument that can apply a constant force to a biomolecule over a range of extensions, and is therefore an ideal tool to study biomolecules and their interactions. However, the video-based tracking inherent to most magnetic single-molecule instruments has traditionally limited the instrumental resolution to a few nanometers, above the length scale of single DNA base-pairs. Here we have introduced superluminescent diode illumination and high-speed camera detection to the magnetic tweezer, with graphics processing unit-accelerated particle tracking for high-speed analysis of video files. We have demonstrated the ability of the high-speed magnetic tweezer to resolve particle position to within 1 Å at 100 Hz, and to measure the extension of a 1566 bp DNA with 1 nm precision at 100 Hz in the presence of thermal noise.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.997

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)0.1260.004

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 head0.225
Teacher spread0.218 · 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