Bibliographic record
Abstract
Perhaps no subject has generated more debate in medicine than the diagnosis of brain death (BD). Writers, philosophers, ethicists, and physicians have focused on different aspects of BD. Nevertheless, no significant advances in the understanding of pathophysiologic mechanisms in BD have occurred over the last decade. American Academy of Neurology (AAN) Practice Parameters defined BD as “the irreversible loss of function of the entire brain, including the brainstem” with three specific criteria: 1) unresponsiveness, 2) absent brainstem reflexes, and 3) apnea. In addition to these clinical criteria, there are important prerequisites: a) presence of clinical or neuroimaging evidence of acute CNS catastrophe severe enough to explain the condition, b) core temperature greater than 32°C (90°F), c) no drug intoxication or poisoning, and d) absence of confounding medical conditions such as severe electrolyte, acid-base, or endocrine disturbances.1 In this issue of Neurology ®, Wijdicks and Pfeifer2 offer a new look at an old condition and attempt to provide an analysis of the neuropathologic features that correlate with a clinical diagnosis of BD. They reviewed macroscopic and microscopic brain pathology for ischemic neuronal damage in 41 patients …
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".