Is the Framework of Cohn's ‘Tritope Model’ for How T Cell Receptors Recognize Peptide/Self‐<scp>MHC</scp> Complexes and Allo‐<scp>MHC</scp> Plausible?
Bibliographic record
Abstract
Cohn has developed the tritope model to describe how distinct domains of the T cell receptor (TcR) recognize peptide/self-MHC complexes and allo-MHC. He has over the years employed this model as a framework for considering how the TcR might mediate various signals [1-5]. In a recent publication [5], Cohn employs the Tritope Model to propose a detailed mechanism for the T cell receptor's involvement in positive thymic selection [5]. During a review of this proposal, I became uneasy over the plausibility of the underlying framework of the Tritope Model. I outline here the evolutionary considerations making me question this framework. I also suggest that the proposed framework underlying the Tritope Model makes strong predictions whose validity can most probably be assessed by considering observations reported in the literature.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".