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Record W2033601599 · doi:10.3166/jesa.44.631-659

Estimation robuste par synthèse H<sub>2</sub>de micro- et nanoforce à l'aide de ressorts magnétiques actifs

2010· article· fr· W2033601599 on OpenAlexvenueno aff
Ali Cherry, Emmanuel Piat, Joël Abadie

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2010
Typearticle
Languagefr
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTransducerSIGNAL (programming language)Compressed sensingNoise (video)Force transducerAcousticsComputer sciencePhysicsAlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

This article deals with the problematic of micro- and nanoforce measurement. The force is the unknown excitatory signal of a transducer whose only the output is measurable. This general problematic of an unknown input signal reconstruction from a noisy output signal is developed inside the H2 synthesis framework. The resulting methodology is implemented in a micro- and nanoforce sensor that uses a macroscopic seismic mass controlled by active magnetic springs. This methodology uses only a very basic knowledge on the force dynamic and thanks to H2 synthesis, ensures that the force estimation remains correct despite the transducer dynamic, the noise measurement, the uncertainty on the force dynamic and the sensor modeling errors.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.273
Teacher spread0.261 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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Same venueJournal Européen des Systèmes Automatisés→Same topicForce Microscopy Techniques and Applications→French-language works237,207→