Bibliographic record
Abstract
Poems syndrome :s a rare multisistemic disorder. It manifestations are Polynueropathy, Organomegaly, Endocrinopathy,and / 01Edema. Monoclonal protein and changes in the Skin. (P.O.E.M.S.)Though some bibliography make no difference with osteoesclerotic mieloma it is considered a real syndrome.The polynueropathy is customarily severe. Although high levels of inrnullo- globulins has been found in the poems, it has not been isolatcd a specific antibody that explain the polynueropathy even though it is strongly suspected.The organomegaly, endocrinopathy, changes in the skin and other systems and involved organs could be in relationship toproducts secreted by plasmatic celis. Wc review the physiopathology and bibliography of the Poems, especially its neurological expression its nosologic location different from osteosclerotic myeloma and a possible relationship to the Herpes Virus S.It was crossed in Medline the terms P.O.E.M.S. and syndrome and were obtained 271 abstracts that were all examined and finallyselected the bibliography considerate meaningful for the objectives. It is presented briefly a case.P.O.E.M.S. is a syndrome that is associated to multiple plasma eclI dyscracia, included the osteoesclerotic myeloma.Prognosis and the treatment vary with the underlying diseasc. As physiopathology of this syndrome is insinuated the action of the interleukines 1- (IL-1 beta) and 6 (IL-6), the vascular growth endothelial factor (VGEF), the tunioral necrosis factor alpha (TNF-alpha) and antibodies anti- nerve. The P.O.E.M.S. is a syndrome with own Palabras claves: Síndrome de POEMS aso- identity. ciado con mieloma múltiple.The Herpes Virus 8 may plays a key rol Material y Métodos to uncover the Poems physiopathology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".