The architecture of the 6-month-old gastrocnemius: a 3D volumetric study
Bibliographic record
Abstract
Gastrocnemius is essential in normal gait, con-tributing to the control of ankle plantarflexion and knee flexion. However, there is a paucity of litera-ture on the architecture of the infant gastrocnemius muscle prior to the onset of weight-bearing and gait. This study investigates the three-dimensional (3D) musculoaponeurotic architecture of the gas-trocnemius in a six-month-old infant. One six-month-old cadaver was used in this study (The University of Toronto Health Sciences Research Ethics Board, #32679, and The University of Auck-land Human Participants Ethics Committee, #016164). Medial (MG) and lateral (LG) heads of the gastrocnemius were serially dissected and a Microscribe G2X™ digitizer used to digitize fiber bundles, aponeuroses and tendons. Data were then exported to Autodesk® Maya® to create 3D models. Custom software quantified architectural parameters, including fiber bundle length, penna-tion angle, physiological cross-sectional area, and muscle volume. The intramuscular architecture was assessed to determine whether musculoapo-neurotic partitions were present. Muscle volume was <1cm3 for both MG and LG. Three architec-tural partitions, proximal, middle, and distal, were identified for both MG and LG. Notably, the proxi-mal partitions of both MG and LG had mean fiber bundle length at 2.21 ± 0.41 cm and 2.22 ± 0.27 cm, significantly greater (p<0.05) than the middle and the distal partitions. The results of this study suggest that both MG and LG have architectural partitions before the commencement of gait. Fur-ther longitudinal studies with larger sample sizes are needed to confirm the presence of these archi-tectural partitions, as well as to investigate their growth across the developmental spectrum.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".