Construction of a linkage map of the Rennell Island Tall coconut type (<i>Cocos nucifera</i>L.) and QTL analysis for yield characters
Bibliographic record
Abstract
AFLP and SSR DNA markers were used to construct a linkage map in the coconut (Cocos nucifera L.; 2n = 32) type Rennell Island Tall (RIT). A total of 227 markers were arranged into 16 linkage groups. The total genome length corresponded to 1971 cM for the RIT map, with 5-23 markers per linkage group. QTL analysis for yield characters in two consecutive sampling periods identified nine loci. Three and two QTLs were detected for number of bunches and one and three QTLs for number of nuts. The correlation of trait values between characters and evaluation periods is partially reflected in identical QTLs. The QTLs represent characters that are important in coconut breeding. The cosegregation of markers with these QTLs provides an opportunity for marker-assisted selection in coconut breeding programmes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.001 |
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".