Bibliographic record
Abstract
The District School Board of Niagara (DSBN) is committed to promoting awareness of safety in schools and recognizes that the health and safety of students are essential preconditions for effective learning. All partners in education, including the Ministry of Education, other Ontario ministries, school boards, administrators, educators, school staff, students, parents, school volunteers, and community-based organizations, have important roles to play in promoting student health and safety and in fostering and maintaining healthy and safe environments in which students can learn. A concussion is defined as: a brain injury that causes changes in the way in which the brain functions and that can lead to symptoms that can be physical (e.g., headache, dizziness), cognitive (e.g., difficulty in concentrating or remembering), emotional/behavioural (e.g., depression, irritability), and/or related to sleep (e.g., drowsiness, difficulty in falling asleep); may be caused either by a direct blow to the head, face, or neck or by a blow to the body that transmits a force to the head that causes the brain to move rapidly within the skull; can occur even if there has been no loss of consciousness (in fact most concussions occur without a loss of consciousness); cannot normally be seen by means of medical imaging tests, such as X-rays, standard computed tomography
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.243 | 0.104 |
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".