Fabrication and Characterization of Nonplanar Microelectrode Array Circuits for Use in Arthroscopic Diagnosis of Cartilage Diseases
Bibliographic record
Abstract
A process to fabricate nonplanar microelectrode array circuits was developed and the microelectrodes were characterized. These platinum microelectrode arrays are for recording streaming potential signals generated during indentation of articular cartilage. The nonplanar substrate was produced by permanent deformation of a 7-in-diameter circular stainless-steel wafer to form 32 semi-spherical caps (radius of curvature = 4.65 mm and height = 250 microm) at the periphery. The wafer was covered with a 2.5-microm-thick layer of insulating polyimide. Standard microelectronic processes were applied to produce 32 circuits (60 mm long x 4 mm wide) with 37 exposed circular microelectrodes (diameter = 100 microm) centered over each semi-spherical cap. A 2.5-microm-thick photodefinable polyimide layer encapsulated the conducting lines. Capacitances between one microelectrode and either another microelectrode or the metallic substrate were 14.6 +/- 2.0 and 34.4 +/- 3.3 pF, respectively, at 100 Hz. The impedance of the microelectrodes in a 0.15 M saline bath (PBS) was 0.25 +/- 0.08 Mohms while the crosstalk (Vinduced/Vapplied) between two microelectrodes was 0.20 +/- 0.11%, at 100 Hz. Indentation measurements were performed on articular cartilage in vitro showing,streaming potentials that indicate electrode-tissue contact times and generation of streaming potentials.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".