Phage Display Technology for Human Monoclonal Antibodies
Bibliographic record
Abstract
During the last 15 years in vitro technologies opened powerful routes to combine the generation of large libraries together with fast selection procedures to identify lead candidates. One of the commonest methods is based on the use filamentous phages. Antibodies (Abs) can be displayed successfully on the surface of phage by fusing the coding sequence of the antibody variable (V) regions to the phage minor coat protein pIII. By creating large libraries, antibodies with affinities comparable to those obtained using traditional hybridomas technology can be selected by a series of cycles of selection on antigen. As in this system antibody genes are cloned simultaneously with selection they can be easily further engineered for example by increasing their affinity (to levels unobtainable in the immune system), modulating their specificity or their effector function (by recloning into a full-length immunoglobulin scaffold). This chapter describes the basic protocols for antibody library construction, handling, and selection.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".