How exaptations facilitated photosensory evolution: Seeing the light by accident
Bibliographic record
Abstract
Exaptations are adaptations that have undergone a major change in function. By recruiting genes from sources originally unrelated to vision, exaptation has allowed for sudden and critical photosensory innovations, such as lenses, photopigments, and photoreceptors. Here we review new or neglected findings, with an emphasis on unicellular eukaryotes (protists), to illustrate how exaptation has shaped photoreception across the tree of life. Protist phylogeny attests to multiple origins of photoreception, as well as the extreme creativity of evolution. By appropriating genes and even entire organelles from foreign organisms via lateral gene transfer and endosymbiosis, protists have cobbled photoreceptors and eyespots from a diverse set of ingredients. While refinement through natural selection is paramount, exaptation helps illustrate how novelties arise in the first place, and is now shedding light on the origins of photoreception itself.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".