Helpful Female Subordinate Cichlids Are More Likely to Reproduce

BACKGROUND: In many cooperatively breeding vertebrates, subordinates assist a dominant pair to raise the dominants' offspring. Previously, it has been suggested that subordinates may help in payment for continued residency on the territory (the 'pay-to-stay hypothesis'), but payment might also be reciprocated or might allow subordinates access to reproductive opportunities. METHODOLOGY/PRINCIPAL FINDINGS: We measured dominant and subordinate female alloparental brood care and reproductive success in four separate experiments and show that unrelated female dominant and subordinate cichlid fish care for each other's broods (alloparental brood care), but that there is no evidence for reciprocal 'altruism' (no correlation between alloparental care received and given). Instead, subordinate females appear to pay with alloparental care for own direct reproduction. CONCLUSIONS/SIGNIFICANCE: Our results suggest subordinate females pay with alloparental care to ensure access to the breeding substrate and thereby increase their opportunities to lay their own clutches. Subordinates' eggs are laid, on average, five days after the dominant female has produced her first brood. We suggest that immediate reproductive benefits need to be considered in tests of the pay-to-stay hypothesis

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Sample sizes of brood care observations per mother.

<p>- = not applicable</p

Spearman rank correlations between the frequency of maternal brood care and frequency of alloparental care by other female group members, in brackets sample sizes (number of broods).

*<p><i>p</i> = 0.022;</p>**<p><i>p</i> = 0.001;</p>***<p><i>p</i><0.001.</p

Reproductive output of subordinate female group members depending on their investment in alloparental care (proportion of total female care), their body size (SL mm), corrected for differences between the experiments (1, 2, 3 or 4).

<p>GEE results with Wald χ², degrees of freedom, <i>p</i>-values and coefficients <i>B</i>±s.e., corrected for group identity effects, and the scaling parameter adjusted using the deviance method. Total number of eggs / 30 days rounded to the nearest integer value. The difference in body size [dominant female - subordinate female] was non-significant at <i>p</i> = 0.75 and removed from the model.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press