MétaCan
Menu
Back to cohort
Record W1877232939 · doi:10.2341/13-361-l

Effects of Temperature and Aging on Working/Setting Time of Dual-cured Resin Cements

2015· article· en· W1877232939 on OpenAlexafffund
Thiago Amadei Pegoraro, Rogério Fulgêncio, L.E. Butignon, AP Manso, RM Carvalho

Bibliographic record

VenueOperative Dentistry · 2015
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsMaterials scienceComposite materialRheometerMixing (physics)CementMaterials testingDentistryRheologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the effects of aging and temperature on working time (WT) and setting time (ST) of several dual-cured resin cements. METHODS: WT and ST were determined with a thermo-controlled stage oscillating rheometer. New cement kits were used for the study. Cements were mixed according to instructions and dispensed on the oscillating stage that was preset at 22°C or 37°C. Rheologic charts were generated from the beginning of mixing until no further oscillation was detected. After initial measurements, cement kits were aged at 37°C for 12 weeks, and WT/ST was determined again at both temperatures. Five samples were read for each material and condition. Data were analyzed with repeated measures analysis of variance and a Tukey test at α=5% for each individual material. RESULTS: The WT and ST of all cements were significantly affected by temperature and aging (p<0.05). In general, higher temperature accelerated WT/ST, but aging effects were material dependent. Some materials presented reduced WT/ST, whereas others showed increased WT/ST, regardless of the temperature. CONCLUSIONS: The WT and ST were significantly affected by temperature variation and aging condition. Although temperature changes appeared to affect all materials similarly, aging effects were material dependent.

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)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
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 head0.013
GPT teacher head0.245
Teacher spread0.232 · 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

Citations15
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueOperative DentistrySame topicConcrete Properties and BehaviorFrench-language works237,207