IMPACT OF BURN SEVERITY, TIME SINCE BURN AND AGE ON THE COGNITIVE FUNCTIONING OF WOMEN WHO HAD BURN INJURIES
Bibliographic record
Abstract
Objective: To investigate the impact of burn severity, time since burn and age on the cognitive functioning of women who had burn injuries. Study Design: Cross sectional study. Place and Duration of Study: Department of Psychology, University of Gujrat, from Nov 2017 to Jul 2018. Methodology: The data were collected from females suffering burn injuries. The burn severity, time since burn and age were assessed to see their impact on cognitive functioning of women with burns injured. Further, Montreal Cognitive Assessment scale was used to measure the construct of cognitive functioning. Results: Among a total of 200 burn victims, 52.5% had the severity level of third degree burns. A total of 75% victims had 6-15 months old burns and 64.5% belonged to age group of 19-34 years. The predictive association among variables based on difference of training and testing relative error (0.61) indicated the significant predictive relationship of burn severity, time since burn and age on the cognitive functioning of burn injured women. Further, relationship of burn severity, time since burn, and age was investigated. The relative importance of burn severity, time since burn and age in predicting cognitive functioning was 0.700, 0.163 and 0.136 respectively. Conclusion: Burn severity, time since burn and age are the factors affecting the cognitive functioning of female burn victims. Whereas role of burn severity was more prominent than time since burn and age.
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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 | 0.001 | 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) | 0.003 | 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".