Characterizing circulating tumor cells using affinity-based microfluidic capture and AFM-based biomechanics
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
Elasticity and bio-adhesiveness of circulating tumor cells (CTCs) are important biomarkers of cancer. CTCs are rare in blood, thus their capture and atomic force microscopy (AFM)-based biomechanical characterization require use of multifunctional microfluidic device. Here, we describe procedures for fabrication of such device, AFM-Chip, and give details on its use in affinity-based CTC capture, and integration with AFM via reversable physical assembly. In the AFM-Chip, CTC capture is efficient, and transition to AFM characterization is seamless with minimal cell loss. For complete details on the use and execution of this protocol, please refer to Deliorman et al. (2020).
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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 it