Bibliographic record
Abstract
This special issue of JCCS is devoted to a special meeting held in London, Ontario to honor the 20th anniversary of the first Canadian Connective Tissue Conference (CCTC). Guest of honor was Robin Poole, who helped organize the initial meeting. To mark this occasion, Robin was presented with a special award designed by David Holdsworth, co-director of the Bone and Joint Institute at the University of Western Ontario. For this issue, Robin has written an article describing the founding and evolution of the meeting and Canadian Connective Tissue Society from a historical perspective. From its inception, the CCTC has focused on trainees, providing a forum for students and postdoctoral fellows to present their data. David O’Gorman and I were honored by being invited by Boris Hinz (of both the Canadian Connective Tissue and European Tissue Repair Societies) to organize the 20th CCTC in London Ontario. Like European-style meetings, the 20th CCTC was organized to break down barriers between faculty and trainees in order to maximize the educational experience. An example of such an event was the introductory mixer at Milos’ Craft Beer Emporium. Such a style of meeting has parallels in similar meetings such as society meetings sponsored by the British Society of Matrix Biology, European Tissue Repair Society, our own International CCN Society as well as the Scleroderma Workshops. If the 20th CCTC was even able to approximate somewhat the style and success of these meetings, then we were successful.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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".