Bibliographic record
Abstract
Cell-cell recognition. A) Cells of the same species tend not to eat each other, unless cannibalism is part of their ecological strategy. Prey species are either randomly selected if they are of the right size, or more commonly, there is some type recognition. As a result, some prey are preferred and others unpalatable. Similarly, symbionts must recognize each other as friendly, because a mistake can be lethal. Roots allow specific Bacteria and Fungi in as endosymbionts or ectosymbionts . An error can cause a lethal infection. The same is true for any symbiosis across protists . B) self-recognition also allows recognition of compatible mating types within mating type clusters. Mating type determination has similarities and differences across protist biology. Sex existed most probably in the early prokaryon, but why was it lost so many times across protists ? Models and experiments indicate that sexualtiy or asexuality both have ecological advantages. The story behind maintaining or losing mating types and sexuality is not clear-cut.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".