An integrated solid-phase extraction system for sub-picomolar detection
Bibliographic record
Abstract
A microchip structure etched on a glass substrate for packed column solid-phase extraction (SPE) and capillary electrochromatography (CEC) is described. A 200 microm long, octadecylsilane (ODS) packed column was secured using two different approaches: solvent lock or polymer entrapment. The former method was utilized for SPE while the latter approach was applied for CEC. In SPE, the ODS packed chamber gave a detection limit of 70 fM for a nonpolar BODIPY (493/503) dye when concentrated for 3 min at an electroosmotic flow rate of 4.14 nL/min, compared to 30 pM for this detector without the SPE step. SPE beds showed reproducible, linear calibration curves (R(2) = 0.9989) between 1 and 100 pM BODIPY at fixed preconcentration times. Breakthrough curves for the 330 pL (ODS-packed) bed indicated a capacity for BODIPY dye of 8.1 x 10(-14) mmol, or 0.25 mmol dye per liter of bed. The ODS-chamber could also be used to analyze dilute amino acid and peptide solutions. In the CEC format, two neutral dyes (BODIPY and acridine orange) were baseline-separated in an isocratic run with a theoretical plate count of 84 (420 000 plates/m) and a reduced plate height of about 1. A labeled peptide was also analyzed by CEC, using the acidic eluent (84% acetonitrile, and 26% aqueous trifluoroacetic acid (0.05%)) preferred for peptide separations on ODS-coated silica particles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.008 |
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".