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Record W7055310305

Cellular Biomechanics Investigated by Atomic Force Microscopy

2004· article· en· W7055310305 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2004
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsViscoelasticityCytoskeletonPlasticityActinMechanosensationMyosinStiffnessDendritic spineIndentation
DOInot available

Abstract

fetched live from OpenAlex

0-494-12945-X L'auteur a accord une licence non exclusive permettant la Bibliothque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par tlcommunication ou par l'Internet, prter, distribuer et vendre des thses partout dans le monde, des fins commerciales ou autres, sur support microforme, papier, lectronique et/ou autres formats.L'auteur conserve la proprit du droit d'auteur et des droits moraux qui protge cette thse.Ni la thse ni des extraits substantiels de celle-ci ne doivent tre imprims ou autrement reproduits sans son autorisation.Conformment la loi canadienne sur la protection de la vie prive, quelques formulaires secondaires ont t enlevs de cette thse.Bien que ces formulaires aient inclus dans la pagination, il n'y aura aucun contenu manquant.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.199
Teacher spread0.189 · 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
Published2004
Admission routes1
Has abstractyes

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