Quantity Analysis on the Characteristic Value of Michelia chapensis Dandy Fruits and Seeds
Bibliographic record
Abstract
Base on the characteristics of the Michelia chapensis Dandy fruits and seeds from Congjiang and Liping seed sources.Through quantity analysis the correlation variable characteristic values of three levels,aggregate follicle,follicle and seed.The results indicated that there are significant differences between the characteristic values of two seed sources.The aggregate follicle of seed source from Liping is thiner and longer,has larger number of follicle,but the seeds are smaller,1000-grain weight is lighter,and the number of per one kilogram pure seeds is larger compared with that from chongjiang.The linear correlation between characteristic values of every levels is better,and all modal passed T-test.The R values of model correlation between aggregate follicle and pure seed weight from two seed sources are 0.897,0.960,and R2 values are 0.804,0.921.The result of regression model variance analysis is found to be significant(p1%).
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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 | 0.001 |
| 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) | 0.001 | 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".