Bibliographic record
Abstract
Over two years, replicate plots of lentils (Lens culinaris L.) were treated before seeding with methabenzthiazuron at a rate of 0.5 kg a.i. ha - 1 . In each year, representative soil, lentil and hay samples were randomly collected from plots of each treatment. Soil samples were tested for residues 24 hrs. after treatment and at harvest. Lentil and hay samples were tested at harvest. A cleanup step was conducted after extraction. Gas chromatograph equipped with a nitrogen/phosphorus detector was used to detect methabenzthiazuron. Overall average of residue levels in soil decreased significantly from 1.16 ′ 0.15 mg kg - 1 , 24 hrs. after treatment, to 0.12 ′ 0.01 mg kg - 1 at harvest. No significant difference in the maximum average residue was found in lentil and hay samples collected from various plots and tested at harvest (0.10 ′ 0.01 and 0.19 ′ 0.02 mg kg - 1 in lentils and hay, respectively). Recovery tests were conducted with each group of samples tested in order to determine the efficiency of the analytical procedure.
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 | 0.000 |
| 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".