Bibliographic record
Abstract
Decades of lack of progress in treating many fatal malignancies of the blood-forming system is commanding interest in new approaches. Targeting early events in the leukemogenic process has long been recognized as likely to offer the information required for these diseases. Analysis of the representation of different mutations in the leukemic cells from individual patients offers a retrospective method to infer their sequence of acquisition and associated subclonal dynamics. An alternative, prospective approach is to exploit strategies for recreating human leukemia de novo using defined genetic methods. This concept is not new, but has been historically difficult to realize. A brief review of our experience in generating insights into the properties and regulation of primitive normal human hematopoietic cells serves as a reminder of how this has enabled our recent advances in developing this approach using both primary sources of chronic myeloid leukemic cells and normal cord blood cells as targets. Decades of lack of progress in treating many fatal malignancies of the blood-forming system is commanding interest in new approaches. Targeting early events in the leukemogenic process has long been recognized as likely to offer the information required for these diseases. Analysis of the representation of different mutations in the leukemic cells from individual patients offers a retrospective method to infer their sequence of acquisition and associated subclonal dynamics. An alternative, prospective approach is to exploit strategies for recreating human leukemia de novo using defined genetic methods. This concept is not new, but has been historically difficult to realize. A brief review of our experience in generating insights into the properties and regulation of primitive normal human hematopoietic cells serves as a reminder of how this has enabled our recent advances in developing this approach using both primary sources of chronic myeloid leukemic cells and normal cord blood cells as targets. This perspective traces some highlights from our laboratory research efforts spanning several decades that have worked toward the long-term goal of improving outcomes of patients with acute myeloid leukemia (AML). It is also written with the purpose of formally recognizing the extraordinary insight and generosity of the Stiftelsen family and the Tobias Foundation they created. Their vision to promote hematopoietic stem cell research as a primary avenue to obtain better treatments of life-threatening blood diseases is unprecedented. Also to be recognized at the outset is the combined effort of an outstanding and dedicated team of trainees and colleagues who played a major role in the work described below. Many of the methods developed to enable primitive normal and malignant human cells to be characterized, as well as key findings thereby enabled, are due to their creativity and efforts. It is an honor and a privilege to link this jointly inspired and executed work with the Tobias Award, necessarily summarized here in very brief form.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".