A BIOCHEMICAL-BASED MODEL FOR THE DOSIMETRY OF DIETARY ORGANICALLY BOUND TRITIUM—PART 1: PHYSIOLOGICAL CRITERIA
Bibliographic record
Abstract
In this paper the physiological criteria for a novel form of model are described whose biokinetics are governed by the overall metabolic reactions of the principal nutrients: carbohydrates, fats, and proteins. The biokinetics of a particular element are based primarily on the oxidation of glucose, fatty acids, and amino acids and the formation of water, carbon dioxide, and urea. The compartmental models proposed follow the pathways of the major elements including hydrogen and, hence, tritium. The parameters for two models of differing complexity--called the HCNO-S and HCNO-C models--were evaluated here on the basis of biochemical reactions; the results of compartmental analysis are reported in an accompanying paper. The simpler form of the HCNO model has single compartments representing the principal nutrients. The more complex model includes compartments representing the longer-term retention of carbohydrates as glycogen, fats as adipose tissue, and proteins in bone and soft tissues. The pool sizes and hydrogen transfer rates are estimated. The incorporation of biochemical reactions and important metabolic parameters serve to give the models a greater semblance of physiological merit than those currently available. For example, ingestion of carbohydrates results in a respiratory quotient of 1.0 and 100% of the hydrogen content oxidized to water, which are the same as values published in the literature. This form of metabolic model enables development of models for other isotopes, besides 3H, of the major elements of the body, e.g., 14C, 15N, 18O.
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
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".