Confocal and STED Live F-actin dataset
Bibliographic record
Abstract
Paired confocal and STED images of F-actin nanostructures in living neurons using the far-red fluorogenic dye SiR-Actin. This dataset was used to train and test the TA-GAN model for confocal-to-STED super-resolution of axonal and dendritic F-actin in living neurons (Resolution Enhancement with a Task-Assisted GAN to Guide Optical Nanoscopy Image Analysis and Acquisition). All images : 20 nm/pixel. Folders: - train : 753 pairs of confocal/STED images (varying sizes) - valid : 47 pairs of confocal/STED images (varying sizes) - test_initial & test_final : 84 confocal/STED pairs acquired before (initial) and 84 acquired after (final) control sequences where 15 confocal images of the full FOV (500 x 500 pixels = 10μm x 10μm) were acquired at 1 frame/minute. In addition to the confocal image, a sub-region (100 x 100 pixels = 2μm x 2μm) was selected outside the central ROI (300 x 300 pixels = 6μm x 6μm) and acquired with the STED modality at every time step; the signal decrease due to photobleaching effects can therefore be more prononced in the border region outside the central ROI. - test_series : contains 149 series of images acquired with TA-GAN assistance using the change-based Dice coefficient threshold or the variability-based threshold. The test_series folder contains folders with names corresponding to "[date of acquisition]_cs[coverslip number]_ROI[selected region number]". Each folder contains three subfolders : input, full_STED, and initial_final_confocal. - Input : this folder contains three-channel images for each of the 15 frames in the series. The first channel is the full FOV confocal image (10μm x 10μm), the second channel is the STED sub-region (2μm x 2μm) with zero-padding to match the shape of the FOV, and the third channel is a decision map of 0s and 1s, with the 1s indicating the position in the FOV of the STED sub-region. - full_STED : this folder contains all the STED FOVs (10μm x 10μm) acquired when triggered by the TA-GAN assistance. The number of full_STED FOVs varies from 0 to 15 per region, with a mean of 2.8 STED images per series. The full FOV STED images acquired before (initialSTED.tif) and after (finalSTED.tif) the series of 15 frames are also included. - initial_final_confocal : The full FOV confocal images acquired before (initialConfocal.tif) and after (finalConfocal.tif) the series of 15 frames.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.016 |
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".