Bibliographic record
Abstract
Alcohol intoxication plays a significant and causal role in various fatal injuries. In comparison to sober individuals, intoxicated people have a greater generic risk for being involved in hazardous activities that may result in fatal injuries. However, it is not clear whether the biological effects of acute alcohol intoxication result in worse injuries than those sustained by sober individuals who are injured by identical mechanisms. Alcohol intoxication has a neuroprotective effect in experimental animal models of traumatic brain injury (TBI) but the evidence for a similar effect in humans is controversial. Earlier studies found such a protective effect, but more recent large epidemiological studies have not confirmed this finding; some studies also suggest a dose-related protective or exacerbating effect of alcohol intoxication on TBI. There are two apparent alcohol-associated syndromes in which an otherwise survivable blunt force impact to the head of an intoxicated individual is fatal at the scene. The first is a fatal cardiorespiratory arrest (the so-called alcohol concussion syndrome or “commotio medullaris”); the second is “traumatic basilar subarachnoid hemorrhage” (secondary to tears in the cerebral arteries, particularly the intracranial and extracranial vertebral arteries).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".