A mixed method study of a peer support intervention for newly diagnosed primary brain tumour patients
Bibliographic record
Abstract
Introduction: Tumour metastases that involve the scalp are unusual.We report the case of a patient with a lung adenocarcinoma that was metastatic to both the skull and the scalp.Case Report: A 61year-old female presented with a scalp mass that increased in size from one cm to 10 cm, over a 7-month period.She had a recent history of 20lb weight loss and anorexia.CT scan revealed a soft tissue mass in the left frontal scalp involving the underlying bone and thickening of dura.Magnetic Resonance Imaging (MRI) three months later exhibited rapid growth of the lytic lesion.Bone scan showed no other primary lesions.Intraoperative biopsy specimen displayed histological characteristics of an adenocarcinoma.The patient was pan-scanned and a primary upper lobe lung lesion with extensive hilar lymphadenopathy was identified.She subsequently underwent operative resection of the lesion and cranioplasty.Pathological examination of tumor biopsy showed a moderately differentiated adenocarcinoma characterized by large irregularly shaped acini embedded in a desmoplastic stroma with a mixed acute and chronic inflammatory infiltrate.Mitotic figures were encountered.The neoplastic cells were immunopositive for CK-CAM5.2,CK 7 and TIF-1 (nuclear), and immunonegative for CK 20, features in keeping with adenocarcinoma.Discussion: We describe an unusual case of lung adenocarcinoma that became metastatic to both skull and scalp.The histopathological features and differential diagnosis of such lesions are discussed in the context of the literature.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".