Generation and Validation of MYTH Baits: iMYTH and tMYTH Variants
Bibliographic record
Abstract
Generation of baits for membrane yeast two-hybrid (MYTH) screening differs depending on the nature of the protein(s) being studied. When using native yeast proteins with cytoplasmic carboxyl termini, the integrated form of MYTH (iMYTH) is the method of choice. iMYTH involves endogenous carboxy-terminal tagging of the gene of interest within the yeast chromosome, leaving the gene under the control of its natural promoter. When studying proteins not native to yeast, or native yeast proteins with only cytoplasmic amino termini, traditional MYTH (tMYTH) must be used. In the tMYTH approach, amino- or carboxy-terminally tagged proteins are expressed ectopically from a plasmid. In this protocol, we describe the generation and validation of iMYTH and tMYTH baits. MYTH bait generation can typically be completed in ∼1-2 wk.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".