Bibliographic record
Abstract
A thorough history and physical examination are fundamental to the assessment of patients with brachial and pelvic plexus tumors. Typical of most peripheral nerve tumors, the presenting symptoms and signs are few, and if present, can be subtle. Presenting complaints may include a palpable mass lesion, either symptomatic or asymptomatic; sensory alterations; pain; motor deficits; visceral symptoms; or autonomic dysfunction. Motor deficits are usually a late feature in the pathogenesis of this lesion, and a progressive course of pain and significant sensory and motor deficits suggests a malignant pathological process. A detailed family history may reveal familial syndromes and neurocutaneous disorders that predispose the patient to neoplasia, such as neurofibromatosis. The physical examination should be conducted in a systematic fashion, looking for any cutaneous features and motor and sensory deficits. The mass should also be examined for form, consistency, and mobility. An irregular, firm, and immobile mass suggests a malignant lesion. Complete and accurate clinical information must be gathered to pinpoint the anatomical localization of the lesion and formulate a differential diagnosis.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".