Immobilized gold nanoparticles fabricated by template assisted organo metallic chemical vapor deposition for oligonucleotide hybridisaton studies
Bibliographic record
Abstract
Immobilized gold nanoparticles on oxide surfaces were prepared by template assisted organometallic chemical vapor deposition (OMCVD). The growth parameters, optical parameters such as the plasmon resonance band, as well as geometrical parameters such as size and shape are investigated by UV-Vis spectroscopy, AFM, TEM and SEM. These new kind of gold nanoparticles were applied on a fluorescence based oligonucleotide hybridization study. Gold nanoparticles with a mean lateral diameter of 12 nm yielding an extinction maximum at around 520-530 nm should be able to resonantly excite the Cy3-fluorescence label attached to the target oligonucleotide. The hybridization reaction is taking place between gold nanoparticle surface-attached oligonucleotide catcher strands and chromophore-labeled target strands in solution. The experiment was conducted in the form of classical total internal reflection fluorescence detection. The kinetic data were quantitatively analyzed following a simple Langmuir model. It was found that a single mismatch between oligonucleotide target and probe reduces the Langmuir equilibrium constant by two orders of magnitude, allowing for an excellent sequence-specific detection of oligonucleotide hybridization based on OMCVD gold nanoparticles.
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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 | 0.000 |
| 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) | 0.001 | 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".