Characterization and Analysis of Healthy and Carious Teeth Through Electrical Measurements
Bibliographic record
Abstract
Tooth carious is a harmful and enduring hurt to parts of the teeth' rigid surface that seem like small holes and cavities.Caries is caused by a summation of factors, such as creating bacteria between teeth, eating soft foods frequently, drinking sweaty drinks, and not brushing the teeth right.The present study aims to design and implement an electrical circuit for measuring the electrical impedances of healthy and carious teeth.Besides, the LCR meter analyser was employed to calculate the electrical average impedance and phase shift of healthy and carious teeth with different frequencies ranging from 0.01 Hz to 10 MHz.The presented study is supported by the scanning electron microscopy (SEM) and the Energy Dispersive X-ray spectroscopy (EDX) test for analysis of the teeth' structure and detect the elements and chemical characteristics of the teeth.The Xray and imaging tests are done using dental radiography X-ray equipment in Al-Karkh General Hospital with the help of dentists.The results of the study showed that with the wide spectrum of frequencies, the electrical impedance averaged value for carious teeth is less than its value in the healthy teeth since the impedance real part is (3.63E+03 to 2.59E+06) Ω and (82.567 to 1.27E+05) Ω for the healthy and carious teeth respectively, with increasing in the frequency range (1.00E-02-8.89E+06)Ω and reducing the phase shift.Since healthy teeth have fewer chemical elements than carious teeth, the EDX test showed the chemical elements of the tooth, including Antimony, Calcium, Phosphorous, Carbon, and Chlorine, in different concentrations.The promising results show that the proposed method is sufficient and reliable to differentiate the carious in early stages, giving a chance to recover and maintain the teeth' health.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".