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Record W2742776345 · doi:10.1101/cshperspect.a028761

Mechanosensing and Mechanotransduction at Cell–Cell Junctions

2017· review· en· W2742776345 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

VenueCold Spring Harbor Perspectives in Biology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsCanadian Nautical Research Society
FundersNational Health and Medical Research CouncilMedical Research CouncilMechanobiology Institute, Singapore
KeywordsMechanotransductionBiologyCell biologyCell adhesionCadherinCellCell junctionCell–cell interactionAdherens junctionAdhesionFocus (optics)Cell mechanicsCytoskeletonPhysicsGenetics

Abstract

fetched live from OpenAlex

Cell adhesion systems are defined by their ability to resist detachment force. Our understanding of the biology of cell-cell adhesions has recently been transformed by the realization that many of the forces that act on those adhesions are generated by the cells that they couple together; and that force at adhesive junctions can be sensed to regulate cell behavior. Here, we consider the mechanisms responsible for applying force to cell-cell junctions and the mechanosensory pathways that detect those forces. We focus on cadherins, as these are the best-studied examples to date, but it is likely that similar principles will apply to other molecular systems that can engage with force-generators within cells and physically couple those cells together.

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 score0.985
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 integrity0.0010.000
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 head0.044
GPT teacher head0.336
Teacher spread0.291 · 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