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Record W2097943906 · doi:10.3390/ma8041778

Bone Regeneration Using Bone Morphogenetic Proteins and Various Biomaterial Carriers

2015· review· en· W2097943906 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

VenueMaterials · 2015
Typereview
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversity of ManitobaUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsBone morphogenetic proteinBiomaterialBone healingRegeneration (biology)Bone graftingCell biologyMesenchymal stem cellStem cellBone morphogenetic protein 2Biomedical engineeringMaterials scienceBiologyMedicineDentistryAnatomyBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Trauma and disease frequently result in fractures or critical sized bone defects and their management at times necessitates bone grafting. The process of bone healing or regeneration involves intricate network of molecules including bone morphogenetic proteins (BMPs). BMPs belong to a larger superfamily of proteins and are very promising and intensively studied for in the enhancement of bone healing. More than 20 types of BMPs have been identified but only a subset of BMPs can induce de novo bone formation. Many research groups have shown that BMPs can induce differentiation of mesenchymal stem cells and stem cells into osteogenic cells which are capable of producing bone. This review introduces BMPs and discusses current advances in preclinical and clinical application of utilizing various biomaterial carriers for local delivery of BMPs to enhance bone regeneration.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
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 head0.036
GPT teacher head0.265
Teacher spread0.228 · 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