Demonstration of a reusable plasmonic polymer microarray sensing platform
Bibliographic record
Abstract
High throughput plasmonic sensors are a popular research field, standard surface plasmon resonance (SPR) instruments can achieve high throughput only in imaging configuration. This leads to consideration of pattern substrates and isolated nanoparticle arrays, both of which have some disadvantages. Spot functionalisation relies upon mask or pin printing to accomplish density, and this increase the complexity of use and standard operating procedures. Both patterned and nanoparticle arrays assay platforms are also commonly single use, unlike some SPR imaging and multi channel angular sensing SPR approaches. The microarray format proposed here is intended for multiple usages and regenerated, with a simple optical readout method. A plasmonic polymer of exquisite refractive index sensitivity and incorporate glass-like physical and mechanical stability provides the sensing element to the platform. Further, the standard sol-gel chemistry is well understood and amenable to easy covalent functionalisation as well as matrix methods such as nitrocellulose for biomolecule fictionalization. Two forms of polymer templating have been developed. For spots greater than 700μm a double side tape method can be applied and for sub 700μm patterned SU-8 and 100nm Aluminum reflective layer allow greater spot resolution. Proof of concept through refractive index sensing 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 | 0.000 | 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) | 0.000 | 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".