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Record W2057741416 · doi:10.1111/prd.12026

Cell adhesion proteins: roles in periodontal physiology and discovery by proteomics

2013· review· en· W2057741416 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

VenuePeriodontology 2000 · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProteoglycans and glycosaminoglycans research
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsConnective tissueCell biologyExtracellular matrixCell adhesion moleculeCell adhesionProteomicsMedicineRegeneration (biology)AdhesionCellFunction (biology)BioinformaticsBiologyPathologyBiochemistryChemistry

Abstract

fetched live from OpenAlex

Adhesion molecules expressed by periodontal connective tissue cells are involved in cell migration, matrix remodeling and inflammatory responses to infection. Currently, the processes by which the biologic activity of these molecules are appropriately regulated in time and space to preserve tissue homeostasis, and to control inflammatory responses and tissue regeneration, are not defined. As cell adhesions are heterogeneous, dynamic, contain a complex group of interacting molecules and are strongly influenced by the type of substrate to which they adhere, we focus on how cell adhesions in periodontal connective tissues contribute to information generation and processing that regulate periodontal structure and function. We also consider how proteomic methods can be applied to discover novel cell-adhesion proteins that could potentially contribute to the form and function of periodontal tissues.

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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