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Record W2130914300 · doi:10.14295/bds.2009.v12i4.640

Influência de diferentes dispositivos de microtração nos valores de resistência coesiva

2010· article· pt· W2130914300 on OpenAlexaff
Ana Carolina Botta, Ana Carolina Rodrigues Danzi Salvia, Lafayette Nogueira Júnior, Carlos Augusto Pavanelli, Clóvis Pagani

Bibliographic record

VenueBrazilian Dental Science · 2010
Typearticle
Languagept
FieldDentistry
TopicDental materials and restorations
Canadian institutionsOntario Shores Centre for Mental Health Sciences
Fundersnot available
KeywordsResistPhysicsHumanitiesMaterials scienceNanotechnologyPhilosophy

Abstract

fetched live from OpenAlex

O objetivo deste estudo foi avaliar a influência de dispositivos de microtração sobre a resistência coesiva de blocos de resina acrílica. Vinte blocos de resina acrílica termopolimerizável (Onda-Cryl Clássico) foram confeccionados e distribuídos em 4 diferentes grupos experimentais (n=5) de acordo com o dispositivo de microtração empregado: G1:Paquímetro modificado; G2: Dispositivo de Andreatta Filho; G3: Dispositivo de Borges; G4: MT-jig. Os blocos foram seccionados em palitos de 1mm2 e submetidos ao teste de microtração (EMIC DL 1000). Os dados foram avaliados pela Análise de Variância e pelo Teste de Tukey, a 5% de significância. Os menores valores de resistência mecânica foram obtidos com os dispositivos de Andreatta Filho (34,22 MPa) e de Borges (34,49 MPa), e os maiores valores com o Paquímetro modificado (49,44 MPa) e o MT-jig (48,40 MPa). Concluiu-se que os valores de resistência mecânica são influenciados pelos dispositivos de microtração utilizados e que não podem ser comparados entre si.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.289
Teacher spread0.281 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2010
Admission routes1
Has abstractyes

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