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Record W4303575235 · doi:10.1016/j.dib.2022.108664

Datasets describing the morphometric evaluation of the adult rat mandible following growth stimulation of the condyle using ultrasound

2022· article· en· W4303575235 on OpenAlexafffund
Yasamin Hadaegh, Tarek El‐Bialy

Bibliographic record

VenueData in Brief · 2022
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsCondyleMandible (arthropod mouthpart)StimulationUltrasoundResearch articleAnatomyOrthodonticsComputer scienceBiologyMedicineRadiologyNeuroscienceZoologyLibrary science

Abstract

fetched live from OpenAlex

Evaluating morphological changes of the mandible due to the unique role of the condyle in mandibular special growth and remodeling pattern is challenging. This data describes a comprehensive evaluation using new techniques to detect morphological changes of the young adult rat mandibles treated by low intensity pulsed ultrasound (LIPUS) comparing to matching controls. Two-dimensional (2D) analysis was performed on digital photographs of the hemi-mandibles using AutoCAD software with high accuracy. The anatomical points which were more determinative and prone to visual illusion were defined with particularity. Selective combination of measurements was done to allow for a thorough morphometric evaluation of the mandible focusing on the condyle and the main direction of condylar and mandibular growth. The procedure was simulated for three-dimensional analysis of virtual models of the hemi-mandibles via Geomagic-Qualify software. In the whole procedures, conditions were strictly standardized to ensure reliability and repeatability. Further Insights, Interpretations and discussions of the present datasets can be find in https://doi.org/10.1016/j.bonr.2021.101122[1].

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.227
GPT teacher head0.351
Teacher spread0.123 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2022
Admission routes2
Has abstractyes

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