An Amplificative Detection Approach for Autocatalytic Sensing of Ethylene
Bibliographic record
Abstract
Amplified sensing offers the potential for high sensitivity; however, the vast majority of molecular strategies involve stoichiometric detection and signal transduction, including numerous recent examples of systems inspired by transition-metal-catalyzed reactions. Activation of latent precatalysts by a target analyte represents an attractive strategy for detecting low-concentration species. Analyte amplification represents another attractive approach, akin to PCR-based assays. Here we report an autocatalytic detection system based on the ethylene activation of Ru-I2 olefin metathesis precatalysts. Signal transduction is amplified by both catalytic ring closing metathesis of profluorescent substrates and ethylene propagation to activate additional units of catalyst. High sensitivity is observed as a result of this dual-mode amplified detection of ethylene. Detection of endogenous ethylene from fruit and oxidation-decomposition of polyunsaturated fatty acids via lipid peroxides is demonstrated.
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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) | 0.000 | 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".