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
Twenty-five years after the discovery of protein kinase C (PKC), the physiologic function of PKC, and especially its role in pathologic conditions, remains a subject of great interest with 30,000 studies published on these aspects. In the cerebral circulation, PKC plays a role in the regulation of myogenic tone by sensitization of myofilaments to calcium. Protein kinase C phosphorylates various ion channels including augmenting voltage-dependent Ca2+ channels and inhibiting K+ channels, which both lead to vessel contraction. These actions of PKC amplify vascular reactivity to different agonists and may be critical in the regulation of cerebral artery tone during vasospasm. Evidence accumulated during at least the last decade suggest that activation of PKC in cerebral vasospasm results in a delayed but prolonged contraction of major arteries after subarachnoid hemorrhage. Most of the experimental results in vitro or in animal models support the view that PKC is involved in cerebral vasospasm. Implication of PKC in cerebral vasospasm helps explain increased arterial narrowing at the signal transduction level and alters current perceptions that the pathophysiology is caused by a combination of multiple receptor activation, hemoglobin toxicity, and damaged neurogenic control. Activation of protein kinase C also interacts with other signaling pathways such as myosin light chain kinase, nitric oxide, intracellular Ca2+, protein tyrosine kinase, and its substrates such as mitogen-activated protein kinase. Even though identifying PKC revolutionized the understanding of cerebral vasospasm, clinical advances are hampered by the lack of clinical trials using selective PKC inhibitors.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it