Transformative Technologies in Glycomics Workshop
Bibliographic record
Abstract
In November 2013, the Consortium for Functional Glycomics (CFG), an international body of researchers seeking to understand the functions of glycans and glycan-binding proteins (GBPs) that impact human health and disease, held a workshop entitled “Development and Applications of Transformative Technologies in Glycobiology” immediately preceding the Annual Meeting of the Society for Glycobiology. The workshop was organized by Christine Szymanski and Brian Cobb and was funded by the National Institute of General Medical Sciences (NIGMS) through a U13 grant (Michael Tiemeyer and James Prestegard, Principal Investigators) that provides support to the CFG working groups for identifying and addressing cross cutting issues facing the field, in order to “promote problem solving,” and develop approaches/solutions that move the field forward. Richard Cummings, the current CFG Director, opened the workshop with a status report. The CFG continues to grow, even after the termination of the original NIGMS glue grant program that it was developed under. Now numbering over 600 members, the CFG is funded through R24 and P41 grants from NIGMS, and remains active through the work of its steering committee, the glycan array core at Emory, the informatics core at MIT, and through the NIGMS U13 meeting grant which supports its subgroup activities and fosters growth in the field of glycomics and glycosciences in general. The workshop focused on the continued evolution of technologies such as glycan arrays, for deciphering the role of glycans, and their binding partners in normal and disease processes, and attracted 88 attendees representing 11 countries, including 8 invited speakers, 4 speakers selected from submitted abstracts, and 27 poster presenters. Two highlighted presentations were provided by glycoscience trainees. Overall, the workshop was a successful exposition of the current state of the art in glycomics research and transformative technologies and it illuminated the needs for additional technology development.
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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 | 0.017 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.024 | 0.015 |
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".