Optimization of Molecularly Imprinted Polymer Method for Rapid Screening of 17<i>β</i>-Estradiol in Water by Fluorescence Quenching
Bibliographic record
Abstract
A new method was optimized for rapid screening of 17β-estradiol (E2) in water under 10 min. Molecularly imprinted polymer (MIP) particles (325 ± 25 nm) were added in a water sample at pH 5.5 and 20°C to form a suspension. Fluorescence emission from E2 nonspecifically bound onto the MIP particles was first quenched by large gold nanoparticles (43 ± 5 nm). The Stern-Volmer plot was linear, with dynamic quenching constants (K(sv)) of 2.9 ×10(4) M(-1). Fluorescence emission from E2 specifically bound inside the MIP particles was next quenched by small nitrite anions that easily penetrated the imprinted cavities. The Stern-Volmer plot became nonlinear, with K(sv) = 2.1 × 10(2) M(-1) and static quenching constant (V) below 1.0 M(-1). The difference between these two emission intensities varied as the initial E2 concentration in water, generating a Scatchard calibration curve with R(2) > 0.97 from 0.1 to 10 ppb.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".