Correction: Inotuzumab ozogamicin in pediatric patients with relapsed/refractory acute lymphoblastic leukemia
Bibliographic record
Abstract
We thank the research coordinators and following physicians at pediatric cancer centers for contributing data to this project: Prashant Hiwarkar and Jayashree Motwani, Birmingham Women's and Children's Hospital, UK; Kelly Malone, Children's Hospital of Colorado, USA; Mylene Bassal, Children's Hospital of Eastern Ontario, Canada; Yoav Messinger and Joanna Perkins, Children's Hospital of Minnesota, USA; Van Huynh, Children's Hospital of Orange County, USA; Richard Ho, Children's Hospital at Vanderbilt, USA; Joanne Chuah and Jessa Morales, Children's Hospital at Westmead, Australia; Donald Wells, Dell Children's Hospital, USA; Nicolas Boissel, Hospital Saint-Louis, France; Tannie Huang, Kaiser Permanente, USA; Stacey Marjerrison, McMaster Children's Hospital, Canada; William Carroll and Joanna Pierro, New York University Langone Medical Center, USA; Ajay Vora, Sheffield Children's Hospital, UK; Donna Lancaster, The Royal Marsden Hospital, UK; Lucie Šrámková, University Hospital Motol, Czech Republic; Chatchawin Assanasen, University of Texas Health Science Center, San Antonio, USA; Rupert Handgretinger, University of Tübingen, Germany.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".