<i>T</i><sub>1</sub> and <i>T</i><sub>2</sub> measurements of the fine structures of the in vivo and enucleated human eye
Bibliographic record
Abstract
PURPOSE: To measure T(1) and T(2) of the fine structures of the in vivo eye. MATERIALS AND METHODS: Involuntary saccades make it difficult to obtain artifact-free images. Using a method recently reported (Bert et al, Acad Radiol 2006;12:368-378), near artifact-free spin-echo images were obtained. Both an isolated enucleated eye and eight human subjects were studied at 1.5 T. Spin-echo variable TR/TE data was acquired for T(1)/T(2) determination. Average relaxation times were calculated two ways. First, an arithmetic average over different subjects was computed. Second, all data was normalized using the fitted amplitudes of each data set and pooled to obtain a single least squares fit. RESULTS: In vivo T(1)/T(2) (msec) are: arithmetic average T(1), T(2), normalized data T(1), T(2). Anterior chamber: 6233 +/- 979, 468 +/- 149, 5053 +/- 1052, 450 +/- 49. Ciliary body: 1916 +/- 184, 80 +/- 7, 2038 +/- 114, 76 +/- 3. Chorioretina: 1717 +/- 500, 72 +/- 25, 1511 +/- 230, 78 +/- 3. Extraocular muscle: 1581 +/- 646, 41 +/- 7, 1470 +/- 231, 41 +/- 1. Iris: 3334 +/- 989, 163 +/- 63, 3376 +/- 338, 153 +/- 10. Lens cortex: 1712 +/- 466, 93 +/- 36, 1413 +/- 177, 100 +/- 5. Lens nucleus: 1133 +/- 40, 26 +/- 3, 1138 +/- 47, 25 +/- 0.4. Optic nerve: 1906 +/- 301, 68 +/- 16, 1805 +/- 244, 71 +/- 2. Posterior chamber: 7915 +/- 4897, 241 +/- 14, 3323 +/- 2154, 251 +/- 38. Vitreous humor: 5768 +/- 1190, 756 +/- 804, 4855 +/- 1846, 390 +/- 8. CONCLUSION: In vivo T(1) and T(2) for many of the fine structures of the human eye have been measured.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".