Phytosociological studies on weed flora in wheat fields of South Bihar, (Bihar) India
Bibliographic record
Abstract
Wheat (Triticum aestivum L.) is the second most important food crop of India next to rice but wheat fields are generally infested with a large number of weeds. Due to their highly competitive ability and allelopathic interference, weeds cause irreversible damage to the crop. Weeds survey and Phytosociological studies have been conducted in the wheat fields of major districts of south Bihar namely Buxar, Rohtash, Bhojpur, Aurangabad, Jahanabad, Nawada, Nalanda, Patna and Gaya, Bihar, India during the period 2014-15 and 2015-16.The survey has been carried out at 100 randomly selected wheat fields and well explored covering all the major wheat growing areas of south Bihar, to identify the weed flora, species composition, density, frequency and importance values index (IVI). Phalaris minor, Chenopodium album, Lathyrus aphaca, Vicia sativa, Cirsium arvense, Anagallis arvensis and Rumex species are dominant in wheat crops. Four major weeds were dominant in all districts of South Bihar viz. Phalaris minor, Chenopodium album, Lathyrus aphaca, Vicia sativa. In canal irrigated area crops are badly affected by Phalaris minor, Parthenium hysterophorous and Polypogon monspeliensis weeds. Canada thistle (Cirsium arvense) weed was found to be increasingly affecting wheat, lentil & chickpea in last five years.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".