Bite Marks: Physical Properties of Ring Adhesion to Skin—Phase 2*
Bibliographic record
Abstract
Bite Marks: This study demonstrated that surface wetness was the most influential factor affecting ring adhesion to skin. Also, chemical depilatories and shaving creams were to be avoided when cleaning the skin. The second phase of this research examines the tensile stress needed to rupture the bond between TAK(®) hydroplastic, three new cyanoacrylates, and pigskin with particular consideration for temperature variations. This study also considers solubility issues of different cyanoacrylates in 10% formalin. Finally, the Dorion Type V bitemark excision technique could significantly reduce the risks of tissue distortion when used in conjunction with the following methods and materials. The skin should be devoid of moisture, razor shaved, and cleaned with dishwashing detergent and 98.9% ethanol while avoiding the use of shaving creams and/or chemical depilatories where ring placement is anticipated. The use of unopened cyanoacrylate is encouraged with Permabond(®) as the cyanoacrylate of choice.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".