First Report of <i>Exserohilum monoceras</i> on Barnyardgrass in Argentina
Bibliographic record
Abstract
Barnyardgrass, Echinochloa crus-galli (L) Beauv., is ranked as the world's third worst weed (2). Punctiform, purplish brown spots were found on leaves and sheaths of 7- to 8-week-old barnyardgrass in a rice crop cultivated in La Plata, Argentina (34° 54′S, 58° 30′W). Individual lesions ranged from 1 to 2 mm diameter. Isolates from the lesions were identified as Exserohilum monoceras (Drechsler) Leonard & Suggs (1) (confirmed by A. Watson, Univ. McGill, Canada). Cultures on potato dextrose agar formed dark green colonies. Conidia were 75 to 135 × 15 to 19 μm, 5- to 7-distoseptate, straight or slightly curved, fusoid, tapering gradually towards the base, pale- to mid-olivaceous brown, with a small protruding plenum-type hilum. Barnyardgrass at the 3-leaf stage was inoculated in a greenhouse with a suspension of 105 conidia per ml of water to confirm the pathogenicity of E. monoceras. Plants were bagged and kept in a humidity chamber for 48 h, at approximately 16°C. After 10 days lesions developed that were similar to those found on infected plants in the field. E. monoceras was reisolated from these lesions. This pathogen is being studied as a biocontrol agent for barnyardgrass in tropical areas (2). References: (1) J. L. Alcorn. Mycotaxon 7:411, 1978. (2) W. Zhang and A. Watson. Can. J. Bot.75:685, 1997.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".