Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite advances in neonatal intensive care, periventricular white matter injury (PWMI) remains the most common cause of brain injury in preterm infants and the leading cause of chronic neurologic morbidity. Factors implicated in the pathogenesis of PWMI during prematurity include hypoxia, ischemia, and maternal-fetal infection. PWMI is recognized increasingly in term newborns who have congenital heart disease. The spectrum of chronic PWMI includes focal cystic necrotic lesions (periventricular leukomalacia [PVL]) and diffuse myelination disturbances. Information about the prevalence, severity, and distribution of white matter lesions has relied heavily on neuropathology studies of autopsy brains. However, advances in magnetic resonance imaging of the neonatal brain suggest that the incidence of PVL is declining; focal or diffuse noncystic injury is emerging as the predominant lesion. Insight into the cellular and molecular basis for these shifting patterns of injury has emerged from recent studies with several promising experimental models. These studies support the suggestion that PWMI can be initiated by impaired cerebral blood flow related to anatomic and physiologic immaturity of the vasculature. Ischemic cerebral white matter is susceptible to pronounced free radical-mediated injury that particularly targets immature stages of the oligodendrocyte lineage. The developmental predilection for PWMI to occur during prematurity appears to be related to both the timing of appearance and regional distribution of susceptible late oligodendrocyte progenitors. It is anticipated that new strategies for prevention of brain injury in preterm infants will develop as a result of improved recognition of changing patterns of injury that reflect specific types of cellular vulnerability.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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 it