Development and Purity Identification of InDel Marker Based on Re-resequencing of
Bibliographic record
Abstract
In order to establish a simple, economic, accurate and reliable method to identify the purity of wax gourd hybrid seeds, an InDel marker characterized by significant differences was developed via whole genome re-sequencing of parent plants of ‘modilong’ wax gourd; Then the developed InDel molecular marker was used to identify the purity of hybrid seeds of ‘modilong’ taking the DNA of its hybrid seeds and parent plants as test DNA, and the obtained results were compared with field identification results. A total of 466 pairs of InDel markers were screened by genome re-resequencing of parent plants of ‘modilong’, and 26 of which with distinct differences were selected to be amplified and both got the strip. Among them, 7 pairs of primers can clearly distinguish the purity of wax gourd samples. The purity of InDel molecular marker identification was more than 99% consistent with the results of field plot planting identification, indicating that the purity results obtained by different methods were highly consistent. The InDel molecular marker screened in this study could be used as the purity identification of wax gourd hybrids.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".