Steps in the investigation and management of low semen volume in the infertile man
Bibliographic record
Abstract
An adequate semen volume of ejaculate fluid is required to transportsperm into the female reproductive tract and allow for fertilizationof the oocyte. Thus, seminal fluid volume is an importantpart of the semen analysis done to investigate male infertility. Inthis article, we review the anatomy and physiology of ejaculation,the various etiologies of low-volume ejaculation (artifactual,structural, functional). We then present a comprehensive algorithmfor the evaluation, diagnosis and treatment of the infertileman presenting with low semen volume.Un volume suffisant de liquide séminal dans l’éjaculat est nécessairepour transporter les spermatozoïdes dans les voies reproductricesde la femme et permettre la fécondation de l’ovule.Ainsi, le volume de liquide séminal est une partie importante del’analyse du sperme effectuée afin d’évaluer la fertilité mâle. Dansnotre article, nous passons en revue l’anatomie et la physiologiede l’éjaculation et les diverses causes (artéfactuelles, structuraleset fonctionnelles) d’un faible volume d’éjaculat. Nous présentonsensuite un algorithme complet pour l’évaluation, le diagnostic etle traitement de l’infertilité dans les cas de faible volume de li -quide séminal.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".