In Situ Analysis of Living Embryonic Stem Cells by Coherent Anti-Stokes Raman Microscopy
Bibliographic record
Abstract
Embryonic stem cells (ESC), derived from preimplantation embryos, are defined by their ability to both self-renew and differentiate into all of the cells and tissues of a mature animal. Efforts to develop methods for in vitro culture of ESC for research or eventual therapeutic applications are hampered by the lack of rapid, nondestructive assays for distinguishing ESC from other (differentiated) cells within a growing culture. Coherent anti-Stokes Raman scattering (CARS) microscopy is shown here to be a sensitive and nondestructive method for identifying mouse ESC based on selective observation of specific molecular vibrations believed to be spectroscopic markers indicating the differentiated vs undifferentiated states of such cells. The nonlinear nature of CARS also permits imaging with subcellular resolution, potentially offering a means by which chemical changes accompanying the early stages of differentiation may be associated with certain intracellular compartments (e.g., nucleus, cytoplasm, membranes). A novel exposure/collection configuration is described, which yields high collection efficiency and low interference from nonresonant background components.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".