Report and Abstracts of the 18th Meeting of the Interuniversity Institute of Myology: Virtual meeting, October 21-24, 2021
Bibliographic record
Abstract
In 2021, as the situation due to COVID-19 pandemic was still uncertain, the 18 th annual meeting of the Interuniversity Institute of Myology (IIM), took place on a virtual platform, following the same organization already tested for the previous edition. Participants from Italy, European countries, Canada and USA included clinicians, scientists, pharmaceutical companies and representatives of patient organizations. Four keynote speakers presented new insights into the modulation of muscle stem cell self-renewal in the treatment of neuromuscular disease, the role of nuclear positioning in muscle function, regeneration and tumorigenesis in the heart and advances on therapies of muscular dystrophies. Young PhD students and trainees presented oral communications distributed in five scientific sessions and posters in two poster sessions. On October 21, 2021, selected young scientists participated in the "High Training Course on Advanced Myology", organized with the University of Perugia, Italy. This course consisted of lectures on muscle regeneration and therapeutic perspectives by internationally recognized speakers, followed by roundtable discussions on "Omics technologies in myology" and "New therapeutic approaches", plus the meeting itself. Young trainees, winners of past IIM conferences, forming the Young IIM Committee, selected one of Keynote speakers and were involved in the organization of scientific sessions and roundtable discussions. The friendly welcoming of the meeting, which has strongly characterized this event and is of great help in facilitating scientific exchanges and stimulating novel collaborations, was the hallmark of the conference this year again, even on virtual platform. Breakthrough studies showing interdisciplinary works are fostering new avenues in the field of myology. This year again, scientists and students attended the meeting at the huger number, challenging the difficulties due to the COVID-19 pandemic. All participants shared the wish to continue and implement IIM meeting with new insights on muscle biology, perspectives in the understanding of the muscle-related diseases and in novel therapeutic approaches. We report here abstracts of the meeting describing basic, translational, and clinical research contributing to the large field of myology.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.165 | 0.082 |
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".