Bibliographic record
Abstract
Cronkhite-Canada 증후군은 매우 드문 질환이며 소화기 전장에 걸친 전장에 걸쳐 발견되는 다발성 용종과 조갑 위축, 피부 색소 침착, 전신 탈모를 특징으로 하는 비가족성 과오종성 용종 증후군이다. 설사, 미각변화, 구강건조, 복통, 탈모 등 초기의 임상양상에 따라 5가지 형태로 질병의 경과를 분류할 수 있다. Cronkhite-Canada 증후군은 영양분 흡수 장애, 저알부민혈증, 반복적인 감염, 패혈증, 심부전, 위장관 출혈 등으로 인하여 전반적인 사망률이 45~60%로 높게 보고되며, 병인이 명확하지 않아 보존적 치료만이 현재 적용할 수 있는 치료법이다. 저자들은 위, 대장 내시경, 소장 캡슐내시경 등을 통한 전장에 걸친 다발성 용종과 이의 조직학적 소견, 조갑 변화, 미각 장애, 탈모 등의 임상증상을 토대로 진단한 55세 여자의 증례를 문헌 고찰과 함께 보고한다.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.053 | 0.004 |
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".