Bibliographic record
Abstract
In the last decade, studies of parental care have rapidly proliferated. This increased interest in parental care has been stimulated by advances in three fields. First, the revolution in molecular biology has generated techniques that are increasingly used by behavioural scientists. Such techniques include DNA fingerprinting, which allows researchers to identify the genetic relatedness between putative parents and offspring, and molecular sex markers that allow researchers to determine the sex of offspring at an early stage before external differences have developed. In addition, gene sequencing, which is now fast and relatively inexpensive, has generated vast quantities of data, which are increasingly used to reveal evolutionary relationships that complement older morphology–based phylogenies. This has led to the second advance: several novel statistical techniques, which include parsimony and maximum–likelihood methods for phylogenetic reconstructions, have been developed to investigate past evolutionary events. These techniques provide new opportunities to examine the origins of parental care behaviour, the direction of parental care evolution and life history traits that may have influenced parental care evolution. Third, mathematical modelling of parental care has matured and now encompasses a range of game–theoretical models, some of which take account of state dependence and stochasticity. There has also been an effort to consider the feedback loops between parenting decisions and mating decisions. Some of these models were motivated by the growing consensus that parental care is one of the main battlefields for conflict between the sexes. New mathematical models have been essential in understanding aspects of these conflicts.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 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".