Absence of sperm meiotic segregation error of chromosomes 1, 9, 12, 13, 16, 18, 21, X and Y in a case of 100 % necrozoospermia
Bibliographic record
Abstract
Varying degrees of necrozoospermia are common findings in cases of male sub-fertility; however, it is rare to find persistent and 100 % necrozoospermia. A case of persistent 100 % necrozoospermia is presented in this paper, where aneuploidy analysis was carried out on sperm. No known associations like thyrotoxicosis, genital infection, spinal injury and diabetes were found. Sperm fluorescent in situ hybridization (FISH) was carded out to evaluate sperm aneuploidy for chromosome 1, 9, 12, 13, 16, 18, 21, X and Y and did not show any excess of aneuploidy over controls. To the best of our knowledge, this is the first attempt on meiotic segregation analysis on 100 % necrozoospermic patient. (Asian J Androl 2003 Jun; 5:163-166 )
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".