Peer Review #2 of "Sexing a sex-role-reversed species based on plumage: potential challenges in the red phalarope (v0.2)"
Bibliographic record
Abstract
Sex-role reversal, in which males care for offspring, can occur when mate competition is stronger between females than males.Secondary sex traits and mate attracting displays in sex-role-reversed species are usually more pronounced in females than in males.The red phalarope ( Phalaropus fulicarius[i]) is a textbook example of a sex-role-reversed species.It is generally agreed that males are responsible for all incubation and parental care duties, whereas females typically desert males after having completed a clutch and may pair with new males to lay additional clutches.The breeding plumage of female red phalaropes is usually more brightly colored than male plumage, a reversed sexual dichromatism usually associated with sex-role reversal.Here, we confirm with PCR-based sexing that male red phalaropes can exhibit both the red body plumage typical of a female and the incubation behavior typical of a male.Our result, combined with previous observations of brightly colored red phalaropes incubating nests at the same arctic location (Igloolik Island, Nunavut, Canada), suggests that plumage dichromatism alone may not be sufficient to distinguish males from females in this breeding population of red phalaropes.This stresses the need for more systematic genetic sexing combined with standardized description of intersexual differences in red phalarope plumages.Determining whether such female-like plumage on males is a result of phenotypic plasticity or genetic variation could contribute to further understanding sex-role reversal strategies in the short Arctic summer.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.009 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.426 | 0.271 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".