Screening for Sexually Transmitted Infection Pathogens in Semen Samples
Bibliographic record
Abstract
The transmission of sexually transmitted infection (STI) pathogens from an infected donor to the recipient of a semen donation in assisted conception may result not only in acute infection but also in long-term reproductive complications or adverse outcomes of pregnancy, including infection of the offspring. Screening for bacterial STI pathogens, Chlamydia trachomatis and Neisseria gonorrhoeae is strongly recommended because these pathogens can cause serious reproductive complications in the recipients of semen donations and infection in their offspring. Screening for these pathogens should be performed using the most sensitive methods, such as nucleic acid amplified tests. False-negative results due to inhibitory substances in the semen sample should be monitored using amplification controls. Where specimen transport is not a problem and culture facilities are available, N gonorrhoeae can also be detected by culture. Laboratories performing screening should subscribe to proficiency programs and have strict quality controls. Although Trichomonas vaginalis, group B streptococcus and genital mycoplasmas have been associated with adverse outcomes of pregnancy, the frequent finding of these organisms in healthy individuals brings into question the validity of mandatory inclusion of these organisms in the screening panel. Although viral STI pathogens and Treponema pallidum - the causative agent of syphilis - may be detected in semen, their presence may be more sensitively detected through antibody testing of the donor. Screening donors for HIV, hepatitis B and syphilis by serology is uniformly recommended in all of the guidelines, but the value of screening either donors or semen samples for cytomegalovirus, herpes simplex viruses and human papilloma viruses is less clear.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".