Crystallogenesis Research for Biology in the Last Two Decades as Seen from the International Conferences on the Crystallization of Biological Macromolecules
Bibliographic record
Abstract
The series of 11 International Conferences on the Crystallization of Biological Macromolecules (ICCBM) took place over the period 1986–2006 in the USA (four times), Germany (two times), China, France, Japan, Spain, and lastly the 11th in Canada in Quebec City. Here we review the first 10 ICCBMs. Their focus was to bring rational approaches to the field of protein crystal growth and thus overcome the rate-limiting step in macromolecular X-ray crystallography. This survey summarizes how the ICCBM series contributed to the emergence of the science of biocrystallogenesis. This was achieved through the joint efforts of scientists from the small molecule crystal growth community and from biochemists, biophysicists, and protein crystallographers. Highlights from each conference are discussed, and scientific synergies are emphasized. While the first conferences focused on fundamentals, especially from the standpoint of physics and biochemical considerations, the more recent conferences stressed applications in structural biology, to advanced methods of crystallization, and of crystal quality improvement. Particular attention will be given to themes that were recurrent through all the ICCBMs: purity and impurities, solution properties of macromolecules under precrystallization conditions, microgravity and assessment of crystal quality, as well as specific trends of practical interest to structural biology.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".