Organ Doses from Chest Radiographs in Tuberculosis Patients in Canada and Their Uncertainties in Periods from 1930 to 1969
Bibliographic record
Abstract
This paper describes a study to estimate absorbed doses to various organs from film-based chest radiographs and their uncertainties in the periods 1930 to 1948, 1949 to 1955, and 1956 to 1969. Estimated organ doses will be used in new analyses of risks of cancer and other diseases in tuberculosis patients in Canada who had chest fluoroscopic and radiographic examinations in those periods. In this paper, doses to lungs, female breast, active bone marrow, and heart from a single chest radiograph in adults and children of ages 1, 5, 10, and 15 y in the Canadian cohort and their uncertainties are estimated using (1) data on the tube voltage (kV), total filtration (mm Al), tube-current exposure-time product (mA s), and tube output (mR [mA s]) in each period; (2) assumptions about patient orientation, distance from the source to the skin of a patient, and film size; and (3) new calculations of sex- and age-specific organ dose conversion coefficients (organ doses per dose in air at skin entrance). Variations in estimated doses to each organ across the three periods are less than 20% in adults and up to about 30% at younger ages. Uncertainties in estimated organ doses are about a factor of 2 to 3 in adults and up to a factor of 4 at younger ages and are due mainly to uncertainties in the tube voltage and tube-current exposure-time product.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".