Diversity of antifungal actinomycetes in various vegetative soils of Korea
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diversity of actinomycetes and their antifungal activities against some plant pathogenic fungi were examined in various vegetative soils from 14 different sites in the western part of Korea. Actinomycete counts ranged from 1.17 x 10(6) to 4.20 x 10(6) cfu x g(-1) dried soil. A total of 1510 actinomycetes were isolated from the soil samples. Streptomyces was predominant in soils with a pH range of 5.1-6.5, 9.1-13.0% moisture, and 9.1-11.0% organic matter. Most Micromonospora, Dactylosporangium, and Streptosporangium were distributed in soils with pH 4.0-5.0, 2.0-9.0% moisture, and 4.0-7.0% organic matter. Actinomadura and nocardioform actinomycetes were abundant in soils with pH 4.0-5.0 and 13.1-20.0% moisture and with 9.1-11.0 and 4.0-7.0% organic matter, respectively. Populations of Streptomyces were predominant in all the soils, but were highest in grassland and lowest in mountain-forest soils. Micromonospora was most abundant in pepper-field soil and nocardioform actinomycetes were highest in rice paddy field soil. Dactylosporangium was predominant in lake-mud sediments and pepper-field soil, Streptosporangium in lake-mud sediments, and Actinomadura in mountain-forest soil. Antifungal actinomycetes were abundant in orchard soil and lake mud. More than 50% of antifungal isolates from most soils were classified as genus Streptomyces. Actinomycete isolates that showed strong antifungal activity against Alternaria mali, Colletotrichum gloeosporioides, Fusarium oxysporum f.sp. cucumerinum, and Rhizoctonia solani were predominant in pepper-field soils, whereas those against Magnaporthe grisea and Phytophthora capsici were abundant in radish-field soils.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it