Bibliographic record
Abstract
In responding to the query of Berbel, Ortega, and Ferris, we estimated the proportion of infants with neonatal tumors who were born with congenital anomalies.1 From 1979–1986, 38 children in Ontario were diagnosed with cancer within the first 30 days of life. In reviewing the infants in the cohort with congenital anomalies, 12 infants had neonatal diagnoses of cancer. We estimate that 31.6% of the neonates with cancer had congenital anomalies registered at the time of birth (95% confidence interval [CI], 15.5–48.7%). This estimate is certainly higher than the range of estimates of 9.6–15% reported by an international working group.2 The estimate may be conservative, as congenital anomalies detected after discharge from hospital may have been missed. As our cohorts came from Ontario-based registries,1 we were unable to study specific etiological factors that account for the increased incidence of cancer in infants with congenital anomalies. The comments of Berbel, Ortega, and Ferris on the etiology of childhood cancer in relation to congenital anomalies are welcome.
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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 | 0.005 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.025 | 0.026 |
| Insufficient payload (model declined to judge) | 0.019 | 0.013 |
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".