Bibliographic record
Abstract
This letter is in response to an article written by Michail Nomikos, Karl Swann and F. Anthony Lai in the Research Highlights section of the Asian Journal of Andrology (AJA). The article is entitled, “Is PAWP the ‘real’ sperm factor?” and was written in response to our article entitled, “Sperm-derived WW domain-binding protein, PAWP, elicits calcium oscillations and oocyte activation in human and mouse,” published recently in FASEB J.1 According to the Science Editor of AJA, “Research Highlight” pieces are brief articles that are meant to report on publications from the primary literature. Along those lines, we were delighted to read an insightful comment on our FASEB article prepared for AJA by Dr. George L Gerton. In stark contrast, we found that the article by Nomikos et al. was a promotion of phospholipase C zeta (PLCζ) as the “real” sperm factor, a molecule Dr. Lai's group has been working on for over a decade. In this article we found several omissions, inaccuracies and mistakes that highlight shortcomings in the study of PLCζ which point to major criteria of a “real” sperm factor that have not yet been addressed for PLCζ.
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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".