A small but real risk of cancer in children from undergoing CT
Bibliographic record
Abstract
Commentary on: Pearce MS, Salotti JA, Little MP, et al. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 2012;380:499–505.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Use of ionising radiation in medical imaging has grown in recent decades. In some populations, its cumulative radiation dose approaches that from all other sources combined. This radiation burden has led to concerns about cancers caused by medical imaging. However, imaging studies expose patients to considerably lower radiation doses, and different types of radiation, than those received by most individuals in populations where we have epidemiological evidence of cancer, such as atomic bomb survivors. This gap in the evidence base has led to the controversy regarding whether radiation from medical imaging is indeed harmful. A recent study by Pearce and colleagues provides epidemiological evidence that radiation … [1]: {openurl}?query=rft.jtitle%253DLancet%26rft.stitle%253DLancet%26rft.aulast%253DPearce%26rft.auinit1%253DM.%2BS.%26rft.volume%253D380%26rft.issue%253D9840%26rft.spage%253D499%26rft.epage%253D505%26rft.atitle%253DRadiation%2Bexposure%2Bfrom%2BCT%2Bscans%2Bin%2Bchildhood%2Band%2Bsubsequent%2Brisk%2Bof%2Bleukaemia%2Band%2Bbrain%2Btumours%253A%2Ba%2Bretrospective%2Bcohort%2Bstudy.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0140-6736%252812%252960815-0%26rft_id%253Dinfo%253Apmid%252F22681860%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/S0140-6736(12)60815-0&link_type=DOI [3]: /lookup/external-ref?access_num=22681860&link_type=MED&atom=%2Febmed%2F18%2F4%2F158.atom [4]: /lookup/external-ref?access_num=000307109000031&link_type=ISI
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.004 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.023 | 0.020 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".