Rapid plastic embedding is compatible with colorimetric detection following whole mount in situ hybridization in plant specimens
Bibliographic record
Abstract
In performing in situ hybridizations, nonisotopic nucleic acid labeling coupled with colorimetric detection offers a safer, easier and more rapid alternative to using radioactively labeled nucleic acid probes and microscopic autoradiography. Whole mount in situ hybridization is also advantageous, because many samples can be processed identically and the reduced handling of specimens greatly reduces the risk of exposing tissues to RNase(s). The thickness of whole mount specimens, however, often prevents accurate determination of sites of expression within specific tissues. Although post-hybridization embedding and sectioning is a solution to this problem, the precipitate formed following the common colorimetric detection procedure is soluble in the organic solvents used for dehydration prior to embedding. We have developed a dehydration and embedding procedure that takes advantage of the compatibility of L.R. White resin containing 10% (v/v) polyethylene glycol 400, and heat polymerized. The addition of the plasticizer allows L.R. White embedded tissues to be sectioned at 10 microm providing excellent signal contrast.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".