Bibliographic record
Abstract
Degenerative disc disease (DDD) is a prevalent condition in our society and billionsof dollars are spent annually to treat patients for the chronic pain associated withthis ailment.1 The lower back pain experienced by DDD is due to a rupture in theouter annulus fibrosus of an intervertebral disc (IVD), typically in the lumbar discs,causing the jelly-like nucleus pulposus to escape from the centre of the disc andinflames the spinal nerves.2 Advances in tissue engineering are beginning to develop anovel method to treat this condition by applying a patch to the annulus that allowsfor cartilage formation and integration resulting in repair of the degenerated disc.For this study, two different methods were used to fabricate a hydrogel. The firstmethod used fibrinogen and thrombin dissolved in PBS that formed a gel beforegenipin dissolved in DMEM was used to cross-link.3 The second method of fabricationused all reagents dissolved in DMEM, and the genipin was allowed to cross-link withthe fibrinogen before thrombin was added to form the gel.4 The two methods werecompared via degradation to determine their stability in conditions similar to thoseexperienced by native IVDs. The results of the degradation in PBS showed that thefirst method of fabrication allowed the gels to last until day 10 before completelydissolving. The gels made using the second fabrication method dissolved by day 3.There was no significant difference on the degradation characteristics due to varyingthe concentration of genipin. This first method was selected to perform a cell-mediateddegradation with human bone marrow mesenchymal stem cells (hbm-MSCs) thatformed gels that lasted over 20 days. These results suggest that genipin cross-linkedfibrin gels seeded with hbm-MSCs produce a stable gel with the potential to be usedto repair a damaged IVD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".