Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A critical factor in the quantitation of mutation induction in vivo is the time interval between treatment and sampling. In order to study mutagenesis in the mammary epithelium, the cell type in which breast cancer arises, we have measured the manifestation time, the minimum time required for the maximum mutant frequency to be achieved, in this tissue. The F1 LacZ transgenic mice (Muta MousexSWR) were treated with N-ethyl-N-nitrosourea (ENU) at 50 mg/kg for five consecutive days and then sampled at 1, 2, 4, 6, 9, or 12 weeks after the last treatment. The LacZ- mutant frequency reached a maximum at 4 weeks post-treatment and did not vary significantly thereafter. Dlb-1- mutations in the small intestine reached a maximum at 2 weeks after treatment and did not vary significantly thereafter. Since the stage of estrus cycle during carcinogen exposure influences the mammary tumor incidence and latency, it was expected that it would also affect mutation induction. To test this, F1 LacZ mice in the estrus or di-estrus stage were treated with an acute dose of 250 mg/kg ENU and sampled 10-13 weeks post-treatment. No statistical difference between the two groups was found, indicating that the effect of estrus on carcinogenesis is not due to variation in the sensitivity of the stage of the mammary gland to mutation.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it