Canadian Education: Demographic Change and Future Challenges.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microelectrode arrays for neural interface devices that are made of biocompatible thin-film polymer are expected to have extended functional lifetime because the flexible material may minimize adverse tissue response caused by micromotion. However, their flexibility prevents them from being accurately inserted into neural tissue. This article demonstrates a method to temporarily attach a flexible microelectrode probe to a rigid stiffener using biodissolvable polyethylene glycol (PEG) to facilitate precise, surgical insertion of the probe. A unique stiffener design allows for uniform distribution of the PEG adhesive along the length of the probe. Flip-chip bonding, a common tool used in microelectronics packaging, enables accurate and repeatable alignment and attachment of the probe to the stiffener. The probe and stiffener are surgically implanted together, then the PEG is allowed to dissolve so that the stiffener can be extracted leaving the probe in place. Finally, an in vitro test method is used to evaluate stiffener extraction in an agarose gel model of brain tissue. This approach to implantation has proven particularly advantageous for longer flexible probes (>3 mm). It also provides a feasible method to implant dual-sided flexible probes. To date, the technique has been used to obtain various in vivo recording data from the rat cortex.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
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 it