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Record W18676786 · doi:10.1136/ip.2008.018374

Mise en forme d'apatites nanocristallines : céramiques et ciments

2005· dissertation· en· W18676786 on OpenAlexaboutno aff
Mihai Banu

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Calcium phosphate ceramics and cements are increasingly used in bone surgery. This manuscript reports firstly shaping of nanocrystalline Ca-P using low temperature processes and secondly the setting process of a mineral cement based on amorphous calcium phosphate. After a general presentation of the main physicochemical properties of the calcium phosphates and of current ceramics and cements, different preparations of nanocrystalline apatites in aqueous media are described and trials of ceramisation have been carried out: mainly simple compaction and natural sintering at different temperatures and very low temperature uniaxial compression. This last method was found to preserve the nanocrystalline character of the Ca-P apatite and to produce ceramics with a high compressive strength. Optimal sintering conditions and the properties of the resulting ceramics were shown to be affected by the chemical modifications of the nanocrystal surface. Several factors affecting the setting of amorphous calcium phosphate – based cements commercialized by ETEX Corporation have also been investigated. The conversion of the amorphous phase into apatite has been shown to be responsible for the setting of phosphocalcium cements. Among the different factors studied (solid/solution ratio, preheating, presence of crystal growth inhibitors, ionic strength of the aqueous phase) only the solid/solution ratio seems to have no noteworthy influence.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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 designBench or experimental
Domainnot available
GenreOther

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

Citations9
Published2005
Admission routes1
Has abstractyes

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