Bibliographic record
Abstract
We are pleased to report that 2003 was a record year for Stem Cells submissions—we received over 170 new manuscripts (a 49 percent increase over 2002). The adoption of the Manuscript Central online submission and review program surely contributed to this accomplishment, as did the fact that Stem Cells earned an enviable ISI Citation Index of 4.034 in 2003. Thanks in great measure to our Editorial Board, Stem Cells currently has more than 100,000 online readers per month, and the journal ranks in the top 10 percent of high‐impact cancer journals. This large global audience and professional recognition is a testimony to the excellence of the Journal's articles. We gratefully acknowledge our Editorial Board members for their expert work in reviewing these manuscripts. And we welcome the newest members joining the board this year: ... It gives us great pleasure to honor Dieter F. Hoelzer, Donald Metcalf, and Fumimaro Takaku by welcoming them to the Comité des Sages Advisory Board for Stem Cells after many years of dedicated service to the Journal.
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 | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.077 | 0.059 |
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".