A Colorimetric Method for Quantifying <i>Cis</i> and <i>Trans</i> Alkenes Using an Indicator Displacement Assay
Bibliographic record
Abstract
Abstract A colorimetric indicator displacement assay (IDA) amenable to high‐throughput experimentation was developed to determine the percentage of cis and trans alkenes. Using 96‐well plates two steps are performed: a reaction plate for dihydroxylation of the alkenes followed by an IDA screening plate consisting of an indicator and a boronic acid. The dihydroxylation generates either erythro or threo vicinal diols from cis or trans alkenes, depending upon their syn ‐ or anti ‐addition mechanisms. Threo diols preferentially associate with the boronic acid due to the creation of more stable boronate esters, thus displacing the indicator to a greater extent. The generality of the protocol was demonstrated using seven sets of cis and trans alkenes. Blind mixtures of cis and trans alkenes were made, resulting in an average error of ±2 % in the percentage of cis or trans alkenes, and implementing E 2 and Wittig reactions gave errors of ±3 %. Furthermore, we developed variants of the IDA for which the color may be tuned to optimize the response for the human eye.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 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".