Bibliographic record
Abstract
In this article,the effects of different plant growth regulators and mineral elements on the pollen germination rate and the growth of pollen tubes of Clausena lansium are analyzed.Experimental results showed that different chemical factors had different effects on the germination rate of mature pollens and the growth of the pollen tubes.Among the three mineral elements B,Ca and Mn,germination rates of mature pollens of Clausena lansium increased in this order BMnCa,while the rates of growth of the pollen tubes followed the order of MnCaB.Plant growth regulators IBA,GA3,and IAA could promote the germination of the pollens,and their effects decreased from IBA to GA3 to IAA.As for the rates of growth of the pollen tubes,the order was GA3IAAIBA.Among the chemical factors,the most significant promotion of the germination rate of the mature pollens of Clausena lansium came from IBA at a concentration of 1.5 mmol/L,which resulted in an increase of 22.6%(equivalent to 322.1 times than that of the control).The most effective promoter for the rates of growth of the pollen tubes,reaching a growth rate of 109.7μm/h per hour,was MnCl2 at 60 mmol/L(equivalent to 22.6 times than that of the control).
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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) | 0.001 | 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 | 0.001 |
| 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".