The Performance of Paralleling Technique and Bisecting Angle Technique for Taking Periapical Radiographs: A Systematic Review
Bibliographic record
Abstract
Periapical radiography is a routine radiographic procedure performed by dentists on a daily basis. It can be taken with two techniques, the paralleling technique (P tech) and the bisecting angle technique (B tech). This systematic review aimed to identify the relevant literature, compare the use of P and B techs across various dental specialties, and determine the most appropriate technique to be used for different purposes in taking periapical radiographs. In January 2023, we searched PubMed, Web of Science, Scopus, and Google Scholar to identify the studies that compared the two radiographic techniques. The search string was: (paralleling AND ("bisecting angle" OR "bisected angle")). Manual reference tracing was also performed to identify the studies potentially missed. After screening, 26 studies were included for the qualitative review. The 26 included studies were published between 1976 and 2021. Ten of the studies were about general dentistry (dental radiology in general applications), whereas another ten studies were related to endodontics, such as working length estimation. Most studies advocated the use of the P tech for general, endodontics, implantology, and other indications. B tech was advocated for patients with a low palatal height. More future studies are needed to evaluate their performance in different scenarios with standardized equipment and radiographic positioning.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".