Ringing in 2007 | Solid statistics will promote development of proteomics
Bibliographic record
Abstract
Ringing in 2007t he first issue of a new year is a happy time with the appearance of our new protein of the year, the eukaryotic initiation factor complex 4F.Specifically, the journal's 2007 cover depicts two core components, eIF4E and eIF4G (residues 393-490), in complex.Thanks to John Gross of the University of California, San Francisco, and Gerhard Wagner of Harvard Medical School for providing the image.The journal team is recovering from another year of hectic growth-an ~60% increase in the number of manuscripts has taken us past 700 submitted for the year.Fortunately, the American Chemical Society has continued its strong support of our journal, and we now have an additional associate editor, Martin McIntosh of the Fred Hutchinson Cancer Research Center.Marty's research is centered in the area of bioinformatics and statistics, particularly in clinical proteomics.Marty will give his perspective of this important and growing area in this editorial.Welcome aboard, Marty!
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.137 | 0.121 |
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".