Erratum: LegumeDB bioinformatics resource: comparative genomic analysis and novel cross genera marker identification in lupin and pasture legume species
Bibliographic record
Abstract
Contig Reference accession (GenBank accession No.) Forward primer Reverse primer Product size (bp) 1 AW684083 CTAAGTAATTCGCTTTCACACCCC TTGGATGACACGGATGAAGA 150 2 BE124337 TGTTTCCACTTGAATCGCAG GATTTACCAACGGCGGAGT 152 3 BF641851 GAAGACACAATGAGTAGCAGAGC GGTGACACAGCAGGTGCAAT 151 4 BE325067 CACTCACACTCAACACACAACA CAAGCTTGAACCAAGCACCT 110 5 BE325413 CGCTTAACATCGCTGTCGT GGTTGTCCATGATTAGCCTCA 165 6 BF648637 TCTATTCCTTTCCGTTTCGC TTGTTCTTCCGTTCTTCGCT 154 7 BG581823 ATTCAAACAAACCCTCGCTG GAAACGCAAACCTTGGAGTC 125 Singlet AJ498090 GGGGAACACTCACTCGTTCA GAAGACATGGATCGAATGGA 184 Singlet AJ501268 CGGGGATATCCACTTGTTGT AAGGTTGCTGCTGTTGTTGA 120 Singlet AJ503505 GTGTTCGTTCGTTCAATCCC TGGCGAGTGACTTTGTAAACC 157 Singlet AW683106 GGGAAAGCAAGCACAGTAGC TGGAGTTAGTGGTAGGAAAAGG 162 Singlet AW685905 GCGAAATCTCGTAGAAAGCG TAGCAACGGACTCCCGATAC 122 Singlet AW690069 TGCTTCAAGACTACATTCCGAG TGATCTCGAACAGGTGAATCAG 142 Singlet BF648270 CCTCCAACAAAAACCACTTCC AGGATCAGCTTCTGGGTCAA 161 Singlet BQ137028 GTCGTCCGGAGATTATTTGG TGCAGAGGTGAGAGGGAGAT 186 Singlet BQ144083 TTTTTACCTCTTTGCCCGTC AAGGGGAAAGGAACAAGGAA 154
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.155 | 0.098 |
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".