Surgical Treatment for Internal Carotid Artery Aneurysms requiring Strategic Selective Clipping or Parent Artery Occlusion/Flow Alteration
Bibliographic record
Abstract
内頚動脈のチマメ様動脈瘤や動脈解離 (A群) あるいは大型瘤 (B群) の手術ではclippingと親動脈閉塞手術の選択が問題になり得る. われわれはA群では再破裂回避が重要と考え, 急性期にバイパス術を併用して頭蓋内trappingを行っている. B群では動脈瘤の状況に応じて, clipping, trapping, blind-alley formation, flow alterationのいずれかに適宜バイパス術を併用している. 成績は比較的良好であったが, バイパス閉塞, 穿通枝障害, コイル塞栓部での血栓形成などの合併症も経験した. バイパス術選択と確実な実施, 親動脈閉塞の方法, 抗血栓剤の選択などが留意点と考える.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".