Kin-recognition shapes collective behaviors in the cannibalistic nematode <i>Pristionchus pacificus</i>
Bibliographic record
Abstract
Abstract Kin-recognition is observed across diverse species forming an important behavioral adaptation influencing organismal interactions. In most species, proximate level mechanisms are poorly characterized, but in the nematode Pristionchus pacificus molecular components regulating its kin-recognition system have been identified which determine its predatory behaviors. This ability prevents the killing of kin however, its impact on other interactions including collective behaviors is unknown. Utilizing pairwise aggregation assays between distinct strains of P. pacificus , we observed aggregation between kin but not distantly related con-specifics. In these assays, only one strain aggregates with solitary behavior induced in the rival. Abolishing predation through Ppa-nhr-40 mutations results in rival strains successfully aggregating together. Additionally, interactions between P. pacificus populations and Caenorhabditis elegans are dominated by P. pacificus which also disrupts C. elegans aggregation dynamics. Thus, aggregating strains of P. pacificus preferentially group with kin, revealing competition and nepotism as previously unknown components influencing collective behaviors in nematodes.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".