Convergent Preparation of DimLe<sup>x</sup> Hexasaccharide Analogues (Eur. J. Org. Chem. 34/2011)
Bibliographic record
Abstract
Abstract The cover picture shows an artist's impression of colorectal cancer cells displaying the tumor‐associated carbohydrate antigen dimeric Lex (dimLex). This hexasaccharide can be targeted for the development of anticancer vaccines that will help the immune system to selectively distinguish cancerous cells (Foe) from noncancerous cells (Friend). An analogue of the dimLex hexasaccharide in which a galactosyl residue was replaced by a glucose unit was prepared. This analogue will be used in the preparation of such a vaccine candidate. This cover picture was designed and produced by Dr. Uwe Oehler, Department of Chemistry, University of Guelph, Ontario, Canada. Details of this work are described in the article by J. L. Hendel and F.‐I. Auzanneau on p. 6864 ff.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".