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Record W2182176704

In vitro comparison of peak polymerization temperatures of 5 provisional restoration resins.

2001· article· en· W2182176704 on OpenAlexaff
Caroline Lieu, Tang-Minh Nguyen, Lise Payant

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials sciencePolymerizationComposite materialCuring (chemistry)Dental restorationMolarAcrylic resinDentistryPolymerMedicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The heat produced by provisional restoration materials may injure the dental pulp. This study measured and compared peak temperatures during polymerization of 5 materials used in the fabrication of provisional restorations. METHODS: The tested materials were 2 self-curing resins (Integrity and Protemp) and 3 dual-cure resins (Iso-Temp, TCB Dual Cure and Provipont DC). A mould the size of a maxillary molar tooth was fabricated to contain 0.5 cc of resin. The temperature rise of the different materials was recorded every 10 seconds over a 10-minute period. RESULTS: The rise in temperature of Integrity (peak temperature of 33.8 degrees C) and Protemp Garant (35.6 degrees C) was significantly higher than the rise in temperature of Iso-Temp (29.5 degrees C), TCB Dual Cure (28.4 degrees C) and Provipont DC (29.5 degrees C). CONCLUSION: Use of the dual-cure resins in provisional restorations may reduce the risk of pulp injury.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.280
Teacher spread0.258 · 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

Citations36
Published2001
Admission routes1
Has abstractyes

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