Modeling elemental strontium in human bone based on <i>in vivo</i> x-ray fluorescence measurements in osteoporotic females self-supplementing with strontium citrate.
Bibliographic record
Abstract
An in-house custom I-125 excited in vivo x-ray fluorescence (IVXRF) system was used to perform bone strontium (Sr) measurements in individuals suffering from osteoporosis and/or osteopenia. These individuals, who were self-administering with Sr supplements of their choice, were measured frequently, ranging from weekly to biweekly to monthly, over four years, as part of the Ryerson and McMaster Sr in Bone Research Study. Based on these data collected, data from eight subjects were used to perform kinetic modeling of Sr in human bone. Power and exponential models were used to model the data based on one and two compartmental systems. Model parameters included: mean normalized baseline bone Sr signal, half-life and bone Sr uptake. A one compartmental exponential model applied to finger and ankle bone measurements gave half-lives of (508 ± 331) d and (232 ± 183) d, respectively, but did not show statistically significant differences (p = 0.087 96). However, the values fall within literature estimates. When a two compartmental model was applied to finger bone measurements, half-lives of (300 ± 163) d and (2201 ± 1662) d were observed. Ankle bone data gave half-lives of (156 ± 117) d and (1681 ± 744) d. A two sample t-test, assuming unequal variances, showed these half-lives to be statistically different in both the finger and ankle bone measurements (p = 0.0147 and p = 0.00711, respectively). Common kinetic parameters amongst the different subjects could not be unambiguously identified due to the wide scatter of data, leading to an inconclusive kinetic model. The wide distribution of data is suggested to be physiological since technical and positioning factors were eliminated as possible causes. This outcome indicates the need for a more controlled study and further understanding of the physiological mechanism of Sr absorption.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".