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Record W2024877971 · doi:10.1155/2013/102816

Laser Doppler Blood-Flow Signals from Human Teeth during an Alignment and Leveling Movement Using a Superelastic Archwire

2013· article· en· W2024877971 on OpenAlexaff
Alvaro Wagner Rodrigues Salles, Adriana Mirian Cotrim Salles, Gessé Eduardo Calvo Nogueira

Bibliographic record

VenueISRN Dentistry · 2013
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsUniversity of Manitoba
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsLaser Doppler velocimetryMedicineBlood flowBasal (medicine)DentistryOrthodonticsMaxillary central incisorMaterials scienceCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Objective. The purpose of this study was to examine alterations in blood-flow signals (BFS) from human teeth during an alignment and leveling phase (superelastic wire 0.014'') in a clinical orthodontic treatment using laser doppler flowmetry (LDF). Materials and Methods. Recordings were made in 12 maxillary left central incisors. The basal value of the BFS from each tooth (without orthodontic forces) was compared with the corresponding values of BFS during four periods of observation: 20 minutes, 48 hours, 72 hours, and one month after the activation of the orthodontic appliance. Results. Statistically significant decrease of BFS was observed at 20 minutes, 48 hours, and 72 hours (P < 0.05). No differences were found comparing BFS on day 30 and the corresponding basal values. Conclusion. Under real clinical conditions, a significant decrease in BFS was verified during the initial phase of the treatment, followed by a recovery on day 30.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.272
Teacher spread0.247 · 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 designObservational
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

Citations18
Published2013
Admission routes1
Has abstractyes

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