Grayscale 4D Biomaterial Customization at High Resolution and Scale
Bibliographic record
Abstract
Abstract Hydrogel biomaterials have proven indispensable for three-dimensional (3D) cell culture but have fallen short in replicating the innate physiochemical complexity of real tissue. Though traditional photolithography affords localized material manipulation, robust methods that govern when, where, and to what extent such phototailoring occurs throughout materials would be profoundly enabling towards fabricating more-realistic 3D tissue constructs. Here, we introduce “grayscale image z-stack-guided multiphoton optical-lithography” (GIZMO) as a generalizable and intuitive strategy to rapidly photomodulate materials in full 3D non-binary patterns at submicron resolutions spanning large volumes (>mm 3 ). Highlighting its versatility, we employ GIZMO to variably photopattern biomolecule release from, protein immobilization to, and degradation within hydrogels based on biologically derived or synthetic grayscale image stacks with unprecedented complexity. We anticipate that GIZMO will enable new opportunities to probe and manipulate cell fates, as well as to engineer complex functional tissue.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".