Bibliographic record
Abstract
DNA-encoded synthesis can generate vastly diverse screening libraries of arbitrarily complex molecules as long as chemical reaction conditions do not compromise DNA's informational integrity, a fundamental constraint that "DNA-compatible" reaction development does not presently address. We devised DNA-encoded reaction rehearsal, an integrated analysis of reaction yield and impact on DNA, to acquire these key missing data. Magnetic DNA-functionalized sensor beads quantitatively report the % DNA template molecules remaining viable for PCR amplification after exposure to test reaction conditions. Analysis of solid-phase bond forming (e.g., Suzuki-Miyaura cross-coupling, reductive amination) and deprotection reactions (e.g., allyl esters, silyl ethers) guided the definition and optimization of DNA-compatible reaction conditions (>90% yield, >30% viable DNA molecules), most notably in cases that involved known (H(+), Pd) and more obscure (Δ, DMF) hazards to DNA integrity. The data provide an empirical yet mechanistically consistent and predictive framework for designing successful DNA-encoded reaction sequences for combinatorial library synthesis.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".