Cloning and Analysis of Fusarium Wilt Resistance Gene Analogs in ‘Goldfinger’ Banana
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Based on the conservative regions of the nucleotide-binding site and the leucine-rich repeat (NBS-LRR) in cloned wilt resistance genes, the polymerase chain reaction with degenerate primers was employed to isolate resistance gene analogues (RGAs) from the genomic DNA of wilt resistance germplasm ‘Goldfinger’ (AAAB) banana. As a result, twenty fragments of RGAs were isolated, which were of expected size (about 530 bp). Analysis of the deduced amino acids of these RGAs show that they share the NB-ARC domain and belong to the non-TIR-NBS class resistance gene candidates, containing 4 conservative amino acid domains, i.e. P-loop (GMGGVGKTT), Kinase-2 (LLVLDDIW), RNBS-B (CKVLFTTRS), and hydrophobic amino acids GLPL (GLPLALKVL). Other results reveal that sequence identity among the 20 RGAs rang from 41.1% to 99.3%, while identity of the deduced amino acid sequences range from 33.2% to 96.3%. The phylogenetic analysis of the RGA nucleotide sequences and the deduced amino acids showed that the 20 sequences could be divided into 5 distinct types. All of the amino acids deduced from the RGAs share a homology of 28%~54% with those deduced from the known wilt resistance genes such as Fom-2, I2C-1, I2C-2 and I2. This result to some degree indicates the conservation of disease resistance gene evolution. Technically, these RGAs isolated in the present study would lay a base for the further cloning of wilt resistance genes in banana, which could also be used as molecular markers for screening candidate wilt resistance genes in banana.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it