Bibliographic record
Abstract
The field of neuroscience has undergone a recent advancement upon the realization that music has a profound effect on brain plasticity. The hypothesis that a person is born with a brain that is “hard-wired” for use has been replaced with the understanding that while the brain has innate tendencies, it is modifiable and adapts in response to experience (Habib & Besson, 2008). Brain plasticity is necessary for cognitive development to continue (The Neuroscience Institute, 2012). Most infants are born with the basic neural networks needed to begin to adapt to their world, including their musical world, and as they grow and learn, neural networks are formed and developed in response to their experiences. The brain, however, does not always develop as expected, and one significant sign is a delay in gross motor coordination. This paper will present research discussing brain areas and structures associated with coordination and those involved in the processing of music, hypothesizing there might be a relationship between the two. This will have implications for further study regarding the effects of music on the brain and the possibility that music can be used to facilitate brain plasticity and assist in the development of coordination skills in those with developmental delays.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".