The Effect of Different Densities of Planting on Morphological Characters, Yield, and Yield Components of Fennel (Foeniculum Vulgare Mill cv. Soroksary)
Bibliographic record
Abstract
In order to study the effect of different densities of planting on yield, yield components and morphological characters ofFennel, an experiment was carried out in Karaj College of agriculture at 2008. Experiment was conducted based oncompletely randomized block design with three replications and five plant densities. Five plants spaces were 10, 15, 20,25, and 30cm. Results indicated that the effect of plant density was not significant on the plant height, seed length andthousand seed weight. However, the effect of plant density on yield, number of umbel per plant and number of mainbranches was significant in 1% level. Maximum yield (2/431kg/plot), minimum number umbel per plant (67.26), andalso minimum number of main branches (3/8) were obtained with maximum plant density. While minimum yield(1/315kg/plot), maximum umbel per plant (166.86) and maximum number of main branches (7/3) were obtained withminimum plant density.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".