Lab-on-a-Chip for Studying Growing Pollen Tubes
Bibliographic record
Abstract
A major limitation in the study of pollen tube growth has been the difficulty in providing an in vitro testing microenvironment that physically resembles the in vivo conditions. Here we describe the development of a lab-on-a-chip (LOC) for the manipulation and experimental testing of individual pollen tubes. The design was specifically tailored to pollen tubes from Camellia japonica, but it can be easily adapted for any other species. The platform is fabricated from polydimethylsiloxane (PDMS) using a silicon/SU-8 mold and makes use of microfluidics to distribute pollen grains to serially arranged microchannels. The tubes are guided into these channels where they can be tested individually. The microfluidic platform allows for specific testing of a variety of growth behavioral features as demonstrated with a simple mechanical obstacle test, and it permits the straightforward integration of further single-cell test assays.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".