Bibliographic record
Abstract
arg Some miRNAs including miR-146 and miR-155 have type 1 motif (ADAMTS-5) [8], whose deletion generated Tardif et al. Arthritis Research & Therapy 2013, 15:R197 http://arthritis-research.com/content/15/6/R197mice resulted in age-related OA-like changes [8]. Of im-portance, miR-140 expression is significantly decreased (CRCHUM), Notre-Dame Hospital, 1560 Sherbrooke Street East, Montreal, Quebec H2L 4M1, Canadabeen linked to arthritis pathologies, such as rheumatoid arthritis [1-3], but miR-140, originally found in cartilage [4], has been linked more specifically to osteoarthritis (OA) [5,6]. miR-140 decreases the expression of genes known to play detrimental roles in OA cartilage. Among them are histone deacetylase 4 [4], which was recently OA-like changes [9,10], mothers against decapentaplegic homolog 3 (SMAD3) [11], a mediator of transforming growth factor-β (TGF-β) signaling reported to be associ-ated with hip and knee OA in European populations [12] and insulin-like growth factor-binding protein-5 (IGFBP5) [5] an important factor in IGF-1 storage in the joint [13] whose increase is associated with reduced car-tilage destruction [14]. Targeted deletion of miR-140 in * Correspondence:
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.457 | 0.319 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".