Assessing bone mineral density in vivo: digitized fluoroscopy and ultrasound
Bibliographic record
Abstract
The genetic component of osteoporosis in caged laying hens is large, and a method for detecting hens susceptible to fracture could be useful in breeding programs. A radiographic absorptiometry film method was modified by video digitization from an image intensifier and computer analysis and termed digitized fluoroscopy (DF). Humeral and ulnar DF values were measured in 165 hens during lay. Relationships (P < 0.001) were seen between DF assessments from 25 wk onward and postmortem measurements at 70 wk. We conclude that DF can detect poor bones in hens early but is problematic. Quantitative ultrasound was also investigated. We measured amplitude-dependent speed-of-sound (Ad-SoS) in the third toe in hens. Nutritional studies revealed Ad-SoS values correlated with postmortem peripheral quantitative computerized tomography, (control group, r = 0.48, P < 0.001; treatment group, r = 0.39, P < 0.001). In caged and free-range hens, Ad-SoS correlated with shear strength (r = 0.33, P < 0.001, all hens) and radiographic density values (r = 0.53, P < 0.001, all hens) measured postmortem. The Ad-SoS values were higher in free-range than in caged hens (1,904 vs. 1,850 m/s, P < 0.001). Ad-SoS measurements were made in hens from a study where divergent genetic selection has produced high and low bone index lines with 92% difference in tibia strength. The value in high bone index hens was higher than in low bone index hens at 32 (P < 0.001), 42 (P < 0.001), 52 (P < 0.05), and 62 wk (P < 0.001) in generation 8. In an Ad-SoS heritability study, heritability estimates ranged from 0.15 to 0.39. We conclude that Ad-SoS is a heritable trait, reflects other bone measurements, and rapidly detects poor bone quality in hens.
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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".