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Record W2048128134 · doi:10.1002/ppap.200700112

Influence of the Chemical Composition on the Phase Constitution and the Elastic Properties of RF‐Sputtered Hydroxyapatite Coatings

2007· article· en· W2048128134 on OpenAlexaff
Rony Snyders, Étienne Bousser, Denis Mušić, Jens Jensen, Stéphane Hocquet, Jochen M. Schneider

Bibliographic record

VenuePlasma Processes and Polymers · 2007
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsElastic modulusMaterials scienceX-ray photoelectron spectroscopyChemical compositionDiffractionAnalytical Chemistry (journal)SputteringBulk modulusStoichiometryPhase (matter)MineralogyComposite materialThin filmChemistryNuclear magnetic resonanceNanotechnologyOpticsPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract We have studied the influence of chemical composition on the constitution and elastic properties of dense radio‐frequency (RF)‐sputtered hydroxyapatite (HA) coatings. The chemical composition was modified by varying the RF sputtering power density (PD). As the PD was increased by 240%, the Ca/P ratio measured by X‐ray photoelectron spectroscopy increased from ≈1.51 to ≈1.82. X‐ray diffraction indicates phase pure hexagonal HA except for the sample prepared at the highest PD where CaO and Ca3(PO4)2 also form. Deviations from the stoichiometric Ca/P ratio result in reduction of the elastic modulus. For Ca/P = 1.51 ± 0.02, the elastic modulus decreases by ≈15%. This may be due to incorporation of Ca vacancies in the lattice, while for Ca/P = 1.82 ± 0.02, the average elastic modulus decreases by ≈10% due to formation of additional phases. magnified image

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.194
Teacher spread0.187 · 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
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

Citations29
Published2007
Admission routes1
Has abstractyes

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