The Alberta score combined with Infant Language Assessment Scale used in rehabilitation for children with ce-rebral palsy
Bibliographic record
Abstract
Objective To observe the Alberta combined with Infant Language Assessment Scale used in rehabilitation for children with cerebral palsy. Methods From Jun.2012 to Jun.2013, 64 cases of cerebral palsy in Children's Hospital Affiliated to Suzhou University were selected according to the different interventions and were randomly divided into an observation group and a control group, 32 patients in each group.The control group underwent conventional rehabilitation training included exercise therapy(mainly Bobath therapy, Ueda therapy) and application Infants Language Assessment Scale for treatment, and the observation group on the basis of the method above, set the action in accordance with Alberta infant motor scale(AIMS) assessment to develop rehabilitation programs.Adhere to 3 hours a day of repeated intensive training.Efficacy in children after treatment was compared, and forceful move and fine motor movements and the changes in development quotient(DQ) before and after treatment were compared between 2 groups. Results The total efficiency of the observation group and the control group was 90.6% and 71.9%, respectively, and there was statistically significant differences between 2 groups(χ2=6.317, P<0.05). After treatment, the DQ of big movement and fine motor in observation group(47.92±7.15, 42.55±8.13) were significantly higher than before treatment(36.18±8.23, 33.71±10.16) and the control group(38.13±8.21, 36.58±8.06), the differences were statistically significant(t=6.235, 5.452, 6.137, 5.243, all P<0.05). Conclusions The combination of the rehabilitation for children with cerebral palsy in infants language Alberta combined score rating scale, help to improve rehabilitation results and motor function in children, which is of recommendation and application. Key words: Cerebral palsy; Alberta score; Infant Language Assessment Scale; Rehabilitation training
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 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".