Endoplasmic reticulum homeostasis—From molecules to organisms: Report on the 14th International Calreticulin Workshop, Saint Malo, France
Bibliographic record
Abstract
The Calreticulin Workshop, initiated in 1994 by Marek Michalak in Banff (Alberta, Canada), was first organized to be an informal scientific meeting attended by researchers working on diverse biological questions related to functions associated with the endoplasmic reticulum (ER)-resident lectin-like chaperone and applied to a wide range of biological systems and models. Since then, this workshop has broadened the range of topics to cover all ER-related functions, has become international and has been held in Canada, Chile, Denmark, Italy, Switzerland, UK, USA, Greece and this year in France. Each conference, which is organized every other year (pending world-wide pandemic), generally attracts between 50 and 100 participants, including both early career researchers and international scientific leaders to favour discussions and exchanges. Over the years, the International Calreticulin Workshop has become an important gathering of the calreticulin and ER communities as a whole. The 14th International Calreticulin Workshop occurred from May 9-12 in St-Malo, Brittany, France, and has been highlighted by its rich scientific content and open-minded discussions held in a benevolent atmosphere. The 15th International Calreticulin Workshop will be organized in 2025 in Brussels, Belgium.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".