Bibliographic record
Abstract
Robert (Rob) Murray Frederickson has been appointed the Managing Editor of Molecular Therapy starting August 26, 2002. He will take over the responsibilities previously carried out by Fintan Steele. Rob obtained his Ph.D. in Biochemistry and Cell Biology in 1994 from McGill University in Montreal, Canada. He then joined Nature magazine as an assistant biology editor. From 1996 to 1998 Rob worked in the laboratory of Stan Fields at the University of Washington in Seattle as a postdoctoral fellow. In 1998 Rob rejoined the Nature group, first as Research Editor for Nature Biotechnology and then as Senior Editor at Nature Medicine. In November 2000, Rob was appointed the Editor and Director of Content Development of the biotechnology web portal Bio.com, based in Berkeley, California. He most recently was the Editorial Manager at LifeSpan Biosciences in Seattle. Rob is also a freelance writer for the Elsevier journal Chemistry and Biology. Rob is fluent in English and French and brings substantial experience in scientific publication. Rob will be based at Elsevier's offices in San Diego, California. The staff of Elsevier, the editorial board of Molecular Therapy, and the members of the American Society of Gene Therapy extend Rob Frederickson a very warm welcome! (Please continue to submit manuscripts to the New York office.)
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.075 | 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".