Bibliographic record
Abstract
Conjunctival melanoma is a rare, potentially lethal cancer that mainly affects fair-skinned individuals. The tumor mostly arises from primary acquired melanosis (PAM) with atypia. The presentation of conjunctival melanoma varies and should be clinically differentiated from an array of ocular surface pigmented and nonpigmented lesions. Mutations in the oncogenes BRAF (V600E) and NRAS, and the tumor suppressor gene NF1, are associated with worse survival. UV signature mutations are frequently observed in the bulbar conjunctival melanoma. The TNM staging classifies conjunctival melanoma according to its location and extent. The treatment of conjunctival melanoma depends on tumor staging. Surgical excision of a localized bulbar or forniceal tumor with the no-tumor-touch technique and margin cryotherapy can be sufficient for local control. Adjunctive radiotherapy options include Proton beam radiotherapy, Plaque radiotherapy for ocular surface melanoma, Orthovoltage (Deep x-ray) radiotherapy for palpebral melanoma, and Megavoltage LINAC-based photon radiotherapy can be used for locally invasive and localized orbital extension of conjunctival melanoma. Topical mitomycin-C eye drops are used for diffuse flat melanoma or PAM with severe atypia. Systemic targeted therapy such as BRAF inhibitors for melanoma with BRAF mutation, and systemic immunotherapy drugs have been recently used for more extensive or metastatic disease. Risk factors for metastasis include: greater tumor thickness, non-bulbar location, low tumor pigmentation, histologic ulceration, >1 mitotic figure per mm2, and adjacent structures invasion. Localized tumors should be excised en block, and incisional biopsy should be avoided, which could lead to local widespread tumor dissemination and subsequent recurrence and metastasis.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".