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Record W2122853611 · doi:10.1002/mabi.201200355

Scaffold Effects on Osteogenic Differentiation of Equine Mesenchymal Stem Cells: An In Vitro Comparative Study

2013· article· en· W2122853611 on OpenAlexaff
Rodolfo Nino‐Fong, Laurie A. McDuffee, Blanca P. Esparza Gonzalez, Manoj Kumar, Erika F. Merschrod S., Kristin M. Poduska

Bibliographic record

VenueMacromolecular Bioscience · 2013
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsMemorial University of NewfoundlandUniversity of Prince Edward Island
Fundersnot available
KeywordsMesenchymal stem cellScaffoldIn vitroChemistryStem cellCell biologyBiomedical engineeringBiologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

The in vitro viability, osteogenic differentiation, and mineralization of four different equine mesenchymal stem cells (MSCs) from bone marrow, periosteum, muscle, and adipose tissue are compared, when they are cultured with different collagen-based scaffolds or with fibrin glue. The results indicate that bone marrow cells are the best source of MSCs for osteogenic differentiation, and that an electrochemically aggregated collagen gives the highest cell viability and best osteogenic differentiation among the four kinds of scaffolds studied.

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 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)0.001
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 score0.047
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.318
Teacher spread0.284 · 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 teacher head, 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

Citations13
Published2013
Admission routes1
Has abstractyes

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