Characterization of quantum dots using capillary zone electrophoresis
Bibliographic record
Abstract
Commercially available quantum dots (QDs) were characterized using CE. The CE instruments were laboratory-built, each being capable of both electrokinetic and hydrodynamic injection. Modes of detection include UV absorption and LIF. The CE-LIF system was further modified to handle microliter sample volumes during injection. Sodium phosphate (5-25 mM, pH 7.5-11) was found to be a good buffer electrolyte. Sodium mercaptoproprionate CdTe/CdS (ADS620) QDs and carboxylic acid CdSe/ZnS (T2-Evitag) QDs yielded high separation efficiencies of N = 1.5x10(6) plates at t(M) = 10 min and N = 1.0x10(5) plates at t(M) = 3.8 min, respectively. Apparently the EDC/sulfo-NHS bioconjugation chemistry worked well with the neutral T2-Evitag QDs, but not so well with the negatively charged ADS620 QDs. This preliminary knowledge will serve as a basis for new CE immunoassay studies of QD-biomolecule conjugates and their immunocomplexes with target analytes.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".