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Record W2884688608

Effect of porous titanium coating thickness on in vitro osteoblast phenotype expression

2011· article· en· W2884688608 on OpenAlexaffvenue
Antônio Canabarro, Grasiele Edilaine Crippa, Mariana Umekita Shirozaki, Eduardo Martins Sampaio, Louis‐Philippe Lefebvre, Paulo Tambasco de Oliveira, Márcio Mateus Beloti, Adalberto Luiz Rosa

Bibliographic record

VenueNPARC · 2011
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAlkaline phosphataseOsteocalcinTitaniumOsteoblastMaterials scienceCoatingIn vitroPorosityIn vivoGene expressionCalciumChemistryNuclear chemistryMetallurgyBiochemistryGeneNanotechnologyComposite materialBiologyEnzyme
DOInot available

Abstract

fetched live from OpenAlex

Aim: This study aimed at determining the effect of different thickness of porous titanium (Ti) coating, 0.5, 1.0 and 1.5 mm thick (PC-0.5, PC-1.0 and PC-1.5), on osteoblast phenotype expression. Materials and methods: Dense Ti discs coated with 0.5, 1.0 and 1.5 mm of porous Ti (PC-0.5, PC-1.0 and PC-1.5, respectively) were fabricated by powder metallurgy process with pore size typically between 50 and 400 μm and porosity of 60%. Osteoblastic cells obtained from human alveolar bone were cultured on dense Ti (D-Ti) and PC-Ti discs for periods of up to 17 days. Results: Cultures grown on PC-Ti exhibited higher cell proliferation rate than on D-Ti. By comparing PC-Ti groups, it was observed statistical differences on culture grown only at day 10 (PC- 0.5

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations3
Published2011
Admission routes2
Has abstractyes

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