Boveri at 100: Theodor Boveri and genetic predisposition to cancer
Bibliographic record
Abstract
One hundred years have passed since the publication of Theodore Boveri's Zur Frage der Entstehung maligner Tumouren [Concerning the Origin of Malignant Tumours]. This prescient publication created the foundations for much of our understanding of the origins of cancer and in particular the genetic basis of some cancers. In his work, Boveri suggested that loss of key cellular attributes, now known as tumour suppressor genes, are a key driver event in the development of cancer and inheritance could play a role in cancer susceptibility. He also predicted that chromosomal (genomic) instability as a key hallmark of cancer. Whilst these key insights that still inform the practice of cancer genetics, they were not the main theme of Boveri's text, which was to describe the role of chromosomal abnormalities in the development of cancer. In making his case he also suggested that genetic information could be contained in distinct packages (genes) that are linearly arranged along chromosomes and that cancers arise from single cells. These remarkably accurate hypotheses add weight to the need to celebrate this landmark publication for its accurate prediction of so much that we take for granted. Here we focus on Boveri's contributions to our understanding of hereditary cancers, which, alongside the astute clinical observations of Paul Broca and Aldred Scott Warthin, were published decades before the field became respectable, yet could still inform anyone studying hereditary cancers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".