Phytotoxicity and persistence of flucarbazone-sodium in soil
Bibliographic record
Abstract
Flucarbazone-sodium, a new herbicide, exhibits high bioactivity at low concentrations. To elucidate potential carryover and crop injury, the behavior of flucarbazone in six Western Canadian soils was studied in the laboratory. A sensitive bioassay was developed for the detection of flucarbazone. Of five crops tested, oriental mustard showed the highest degree of root and shoot inhibition from the presence of flucarbazone in soil. Flucarbazone concentrations as low as 1 μg kg−1 were detected by the mustard root inhibition method. This bioassay was used to examine phytotoxicity and persistence of flucarbazone. Phytotoxicity was related to soil organic carbon content. Concentrations corresponding to 50% inhibition (I50 values) were estimated after fitting the data to a log-logistic model. I50 estimates ranged from 6.0 to 27.5 μg kg−1 for soils containing 1.1 to 4.3% organic carbon, respectively, and were correlated (R = 0.979) with percent organic carbon in the investigated soils. Persistence of flucarbazone was examined in soils incubated at 25 C and moisture content of 85% field capacity (FC). Flucarbazone dissipation followed first-order kinetics in one soil, but a two-compartment model provided the best fit for dissipation in the other soils. Half-lives (t0.5), calculated from dissipation curves in each soil, ranged from 6 to 110 d. Half-lives were correlated (R = 0.776) with soil organic carbon. Flucarbazone dissipation was more rapid in soils containing less organic carbon. Flucarbazone was more persistent in drier soil; t0.5 was 11 d in soil at 85% FC and was 25 d in soil at 50% FC. Soil characteristics and environmental conditions will affect the degree of plant injury to sensitive crops the year after flucarbazone application.
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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 | 0.000 | 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) | 0.000 | 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".