Organ Distribution of Radioactivity and Disappearance of Radioactivity from Plasma After Administration of [ <sup>3</sup> H] Luteinizing Hormone-Releasing Hormone to Mice and Rats
Bibliographic record
Abstract
Whole-body autoradiography of amouse 5 min after an intrajugular injection of 43 nmoles of l-(4-[3H]pyro-Glu)-LH-RH (18.3 Ci/mmole) shows a large accumulation of radio-activity in the pituitary, subcutaneous tissue, intestinal wall, kidney, and bladder. Some radioactivity is also found in the liver, lungs, and heart, but no labeling is seen in the central nervous system. Direct measurements of radioactivity in different organs of the rat 5 min after injection of [3H] LH-RH also show that the highest accumulation of radioactivity is in the anterior pituitary gland, kidney, epididymal fat, and skin. Low labeling is measured in the posterior (including intermediate) lobe of the pituitary, pineal, liver, submaxillary gland, testis, adrenal, thyroid, and striated muscle. The pattern of plasma radioactivity after a single intravenous injection of [3H] LH-RH can be represented by the sum of four exponents, suggesting a four-compartment model of the disappearance of radioactivity from plasma. The metabolic clearance rate is 1.2 ml/min. The half-life of the first exponent (up to 10 min after injection) is about 7.5 min. 30 sec after injection of [3H] LH-RH, the radioactivity is distributed in a total volume of 26.5 ml (approximately 11% of body weight).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".