Additional file 3 of Identification of the distribution of human endogenous retroviruses K (HML-2) by PCR-based target enrichment sequencing
Bibliographic record
Abstract
Additional file 3: Fig. S2. Identification of HERV-K (HML-2) loci after filtering using a CPM ≥ 50. (a) Venn diagram exhibiting the interrelationship among the detected loci of different individuals. There are still 712 loci detectable after the filter. (b) Linear graph exhibiting the different number of raw reads that were extracted to calculate the number of detectable loci. (c-e) Venn diagram exhibiting the interrelationship among the detected loci of experimental replicates of different individuals. Within the 3 replicates of “P”, 566 loci could be detected in all the repeats, while in “W” and “Y”, there were 563 and 567 loci. (f–h) Correlation analysis of the relative abundance (CPM values) of the same loci in different samples (as in Fig. 3f–h).
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.861 | 0.230 |
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".