Bibliographic record
Abstract
Background: Radiologic imaging has become integral in not only the detection and diagnosis of subdural hematoma, but also in guiding potential treatment options. Particularly, in the arena of chronic subdural hematoma, which has conventionally been managed via surgical drainage, although is shifting toward procedural intervention with embolization of the middle meningeal artery. This paper aims to review the imaging manifestations of subdural hematoma as a function of chronicity, standardized methods of measurement, and identifying the middle meningeal artery and its clinically significant variant anatomy as it pertains to embolization planning. Methods: A literature search using key terms and titles was conducted for articles containing imaging characteristics of subdural hematoma, approaches to measurement, and middle meningeal artery anatomy as the primary focus. Results: The expected evolution of subdural hematoma over time encompasses a broad array of imaging characteristics. Attempts at standardizing hematoma measurements include width, volume, and midline shift. Given the implication of the middle meningeal artery in potential therapeutic embolization, familiarity with its anatomy is vital not only for mapping access, but also for delineating possible dangerous collaterals. Conclusions: Equipped with a more comprehensive approach to characterizing subdural hematoma, the radiologist will be able to curate findings of greater utility to the clinician.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".