Dataset: CODEX highly multiplexed tissue imaging in pancreas
Bibliographic record
Abstract
Human pancreas This dataset was acquired using CODEX, multiplexed single-cell imaging technology for spatial profiling, where all image data is in .tif format and it includes an associated imaging metadata .csv file. The combination of the targets present in this experiment define some of the main cell types and anatomical structures in human pancreas tissue. This dataset is a 12-highly multiplexed experiment performed on a human pancreas 5 μm section including the nuclear marker Hoechst and antibodies conjugated with oligo-sequences directed against the individual markers. Images were acquired using a Leica DMi8 widefield microscope, a digital CMOS camera (Hamamatsu, ORCA-Flash4.0 V3), and a 20x (0.75) NA dry objective. The light source was a SOLA-SM-II. All images were captured at a 16-bit depth with the following dimensions: x (0.325 μm), y (0.325 μm), and z (1.5 μm). In addition, images were processed, tiled and merged using the CODEX® Processor application (CODEX Processor 1.7.0.6).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.046 |
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".