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Record W2043267873 · doi:10.1088/1748-6041/2/1/s03

MEMS capacitive force sensors for cellular and flight biomechanics

2007· review· en· W2043267873 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.

Bibliographic record

VenueBiomedical Materials · 2007
Typereview
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCapacitive sensingMicroelectromechanical systemsCell mechanicsNanotechnologyComputer scienceMaterials scienceAccelerometerCellBiology

Abstract

fetched live from OpenAlex

Microelectromechanical systems (MEMS) are playing increasingly important roles in facilitating biological studies. They are capable of providing not only qualitative but also quantitative information on the cellular, sub-cellular and organism levels, which is instrumental to understanding the fundamental elements of biological systems. MEMS force sensors with their high bandwidth and high sensitivity combined with their small size, in particular, have found a role in this domain, because of the importance of quantifying forces and their effect on the function and morphology of many biological structures. This paper describes our research in the development of MEMS capacitive force sensors that have already demonstrated their effectiveness in the areas of cell mechanics and Drosophila flight dynamics studies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.347
Teacher spread0.312 · 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