Experimental study on the treatment of tibial fractures with biological hot melting adhesive and allogeneic bone plates
Bibliographic record
Abstract
Objective To observe the curative effect and the feasibility of the treatment of tibial fractures with biological hot melting adhesive and allogeneic bone plates in dogs.Methods Thirty-two Labrador dogs'tibia were cutten by saw to make transverse fracture models.They were randomly divided into two groups,adhesive fixation group(16 dogs)treated with biological hot melting adhesive and allogeneic bone plates,and metal plate fixation group(16 dogs)treated by internal fixation of metal plates and screws.Operative time and estimate blood loss were recorded in two groups.Dogs were killed at 2,4,8,12 weeks after the treatment.Gross anatomic observation and X-ray were underwent and compared in two groups.At the same time,mechanical features of tibial samples after adhesive fixation were examined in adhesive fixation group.Results Between the groups there were statistical differences in operative time and estimate blood less(P0.05).Fractures in two groups all healed at 12 weeks after surgery.Conclusion Treatment of tibial fractures with biological hot melting adhesive and allogeneic bone plates has the advantage of short operative time,less surgical injury and rigid fixation which can provide similar therapeutic effects as metal plates.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".