Yield trait improvement of bay scallops following complete diallel crosses between different scallop stocks
Bibliographic record
Abstract
This study describes the complete diallel hybridization between newly introduced bay scallop stock(W) from Canada and local commercial stock(D) grown under laboratory conditions, in China. Larval survival and growth during all life stages(larvae, spat, and adult) were compared among hybrid(DW, WD) and purebred(DD, WW) populations. Signifi cant heterosis was detected for survival during the larval stage(1% of the mid-parent values). The mean heterosis( H m) varied in growth throughout the life span. More than 50% of the H m values were positive and negative in the DW and WD groups, respectively. The infl uence of maternal effects and mating types(intrapopulation vs. interpopulation crosses) on growth for all life stages was not consistent. Larval survival did not differ signifi cantly( P 0.05) with maternal effect or mating type. In the harvest stage, shell length(SL), shell height(SH), shell width(SW), and total weight(TW) were larger in the hybrid compared with the inbred groups. Positive H m values were observed in SL(1.5%), SW(5.8%), and TW(12.3%), and were more signifi cant in the DW groups(6.1%, 4.5%, 6.8%, and 27.2%). These results suggest that hybridization between two geographic populations is a good tool for improving bay scallop growth. However, unstable heterosis between the two populations requires further study.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".