Learning about gravity: segmental assessment of upright control as infants develop independent sitting
Bibliographic record
Abstract
The question of how infants attain upright sitting is at the core of understanding the development of most functional abilities. Our simple, practical method of securing the hips and different trunk segments while evaluating the infant's ability to vertically align and stabilize the trunk in space contributes a useful method and new insights into the development of upright control. Previous studies have considered the trunk to develop as a single segment. The goal of the present study was to examine how postural control changes across multiple trunk segments during typical development (TD) of sitting balance. For this purpose, electromyography (EMG) and kinematic data were collected at four levels of trunk support (axillae, midribs, waist, hips), in a longitudinal study of eight TD infants (3-9 mo of age). We found that developmental changes in stability were specific to the region of the trunk being investigated, changes in antagonistic muscle activity differed for the anterior-posterior versus the medial-lateral axis, and the relationship between muscle activation and movement changed from erratic attempts to gain upright position to anticipatory graded responses as infants developed upright control through a four-stage behavioral process. This information can be used by researchers to further refine hypotheses regarding this developmental process and by clinicians who wish to develop and test more specific treatment programs for children with postural dysfunction.
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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 | 0.002 |
| 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) | 0.001 | 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".