The plasticity of immunoglobulin gene systems in evolution
Bibliographic record
Abstract
The mechanism of recombination-activating gene (RAG)-mediated rearrangement exists in all jawed vertebrates, but the organization and structure of immunoglobulin (Ig) genes, as they differ in fish and among fish species, reveal their capability for rapid evolution. In systems where there can exist 100 Ig loci, exon restructuring and sequence changes of the constant regions led to divergence of effector functions. Recombination among these loci created hybrid genes, the strangest of which encode variable (V) regions that function as part of secreted molecules and, as the result of an ancient translocation, are also grafted onto the T-cell receptor. Genomic changes in V-gene structure, created by RAG recombinase acting on germline recombination signal sequences, led variously to the generation of fixed receptor specificities, pseudogene templates for gene conversion, and ultimately to Ig sequences that evolved away from Ig function. The presence of so many Ig loci in fishes raises interesting questions not only as to how their regulation is achieved but also how successive whole-locus duplications are accommodated by a system whose function in other vertebrates is based on clonal antigen receptor expression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".