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Record W2120176449 · doi:10.1002/jbm.b.20042

Transmittance of a bioceramic dental restorative material based on calcium aluminate

2004· article· en· W2120176449 on OpenAlexaff
Håkan Engqvist, Jesper Lööf, Stina Uppström, M. W. Phaneuf, Jacob C. Jonsson, Leif Hermansson, Nils‐Otto Ahnfelt

Bibliographic record

VenueJournal of Biomedical Materials Research Part B Applied Biomaterials · 2004
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsFibics (Canada)
Fundersnot available
KeywordsMaterials scienceTransmittanceComposite materialBioceramicCeramicAluminateGlass ionomer cementCementComposite numberRadiodensityWavelengthOptoelectronics

Abstract

fetched live from OpenAlex

This article investigates the transmittance of a new ceramic filling material as a function of time, thickness, wavelength, and addition of pigments. In the hardened state the ceramic material is composed of hydrates, calcium aluminate, and glass fillers. The radiopacity of the investigated material is also measured. The results of the transmittance are compared to a commercial glass ionomer cement (Fuji II) and resin composite (Tetric Ceram). The transmittance increased with time from low values after 1 h to values close to the glass ionomer cements after 1 week. The resin composite had almost twice the transmittance as the calcium aluminate material and the glass ionomer cement. The amount of light passing through the material was dependent on both the sample thickness and the wavelength. Samples of 0.5-mm thickness transmitted almost twice as much as 1-mm-thick samples. Regarding the wavelength, blue light was scattered very effectively (low transmittance), whereas red light was not (high transmittance). Addition of pigments lowered the transmittance. The radiopacity was slightly higher than that of enamel.

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 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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.368
Teacher spread0.315 · 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 teacher head, not a consensus.

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

Citations14
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biomedical Materials Research Part B Applied BiomaterialsSame topicDental materials and restorationsFrench-language works237,207