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Record W2833100370 · doi:10.1080/02670844.2018.1491510

Optimisation of fluorapatite coating synthesis applied to a biodegradable substrate

2018· article· en· W2833100370 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

VenueSurface Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversité Laval
FundersEuropean Social Fund
KeywordsFluorapatiteMaterials scienceCoatingSubstrate (aquarium)Fourier transform infrared spectroscopyChemical engineeringApatiteMetallurgyNuclear chemistryMineralogyComposite materialChemistry

Abstract

fetched live from OpenAlex

Fluorapatite was synthesised using the sol–gel route at three different pH values and aged for a number of days. The coating that was determined to be of optimal morphology was then applied to a pure iron substrate and to an austenitic stainless steel, the latter serving as a control. Deposited fluorapatite coatings were characterised by means of X-ray diffraction and Fourier transform infrared spectroscopy. Crystalline fluorapatite was successfully produced at temperatures as low as 250°C. Temperatures of 250°C and higher caused carbonated fluorapatite, present at 150°C, to transform into fluorapatite. Neutralisation of the sol before coating was found to give rise to a less soluble product when immersed in Hank’s solution at 37°C and 5% CO2. Coatings on pure iron and stainless steel substrates were produced by neutralising the sol to pH 7 and heat treatment at 250°C. This generated a morphology which could potentially aid in cellular attachment.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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