Mechanisms that can cause population decline under heavily skewed male-biased adult sex ratios
Bibliographic record
Abstract
人間の活動がきっかけで、動物集団中の成熟した雌と雄のバランス（以降は、性比と記します）が不自然に歪むことがあります。本研究では、雌だけが漁獲されている甲殻類を対象に、性比の歪みが原因となって集団の存続可能性が下がるメカニズムを明らかにしました。雌に対して雄が多くなりすぎると、つまり、性比が雄側へ歪むと、雄による過剰な繁殖行動が原因で、雌が正常に産卵できなくなることを示しました。また、性比が雄側へ歪むと、繁殖できない雄が増え、集団全体の遺伝的多様性が下がりうることを示しました。本研究では、性比が一方の性へ偏ることで雌雄両方の繁殖成功が下がり、結果として集団の存続可能性に負の影響があることを論じています。
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".