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Record W2113200024 · doi:10.1177/0883911511406327

Gradient patterning and differentiation of mesenchymal stem cells on micropatterned polymer surface

2011· article· en· W2113200024 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

VenueJournal of Bioactive and Compatible Polymers · 2011
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
FundersConnaught Fund
KeywordsMicropatterningMesenchymal stem cellChondrogenesisCell biologyCellStem cellCellular differentiationChemistryBiophysicsMicrocontact printingCell growthCell cultureNanotechnologyMaterials scienceBiochemistryBiology

Abstract

fetched live from OpenAlex

A micropatterned surface with different area ratios of cell-adhesive to nonadhesive surfaces was prepared by micropatterning poly(vinyl alcohol) on a polystyrene plate using photolithography. A gradient pattern of mesenchymal stem cells of different cell densities was generated by culturing the cells on a micropatterned surface. The effects of the cell density gradient on cell functions such as proliferation and differentiation were investigated. Cells seeded at a low density proliferated faster than cells seeded at a high density. Although mesenchymal stem cells seeded at both low and high densities showed osteogenic differentiation, the higher cell seeding density could initiate osteogenic differentiation at a faster rate than the low cell density. And high cell density was required to induce chondrogenic differentiation.

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 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 score0.119
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.029
GPT teacher head0.233
Teacher spread0.204 · 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