Assessment of Intra‐ and Intercostal Variation in Rib Histomorphometry: Its Impact on Evidentiary Examination<sup>*</sup>
Bibliographic record
Abstract
Rib histological age estimation requires the evaluation of the middle third of the sixth rib. Human ribs have thin cortices and, when recovered, are often fragmented or absent, making it difficult to identify a specific midthoracic rib. This research explores the amount of microstructure variation in the middle third of the midthoracic ribs and determines whether the sixth rib age prediction equation can be applied to non-sixth ribs with similar accuracy. The amount of variability must be evaluated in order to meet the criterion for evidentiary examination. The sample consists of 120 cortical bone cross-sections from the middle third of ribs 3-8 removed from 20 cadavers. For each rib, osteon population densities (OPDs) and associated age estimates were calculated. The results demonstrate that non-sixth ribs can provide similar OPD values compared with those of the sixth ribs; however, individual variation proved to be significantly associated with bias, suggesting that individual factors influence the magnitude and direction of bias in non-sixth rib OPD values. This demonstrates the importance of evaluating multiple cross-sections (both intra- and inter-rib) to estimate age due to the normal remodeling variation within individuals.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".