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
소면적으로 재배하고 있는 뽕밭의 문제잡초 현황을 파악하고 잡초방제의 기초자료로 활용하기 위하여 경기 수원, 전북 부안을 중심으로 2014년 5월, 7월, 9월에 3회에 걸쳐 뽕밭에 발생하는 잡초를 조사하였다. 뽕밭에 발생하는 잡초는 37과 153초종으로 국화과 37종, 벼과 17종, 마디풀과 14종, 메꽃과 10종, 배추과 8종 등의 순이었다. 이들 잡초를 생활형으로 구분하면, 일년생 68종, 월년생 39종, 다년생 46종이었다. 지역별 발생잡초를 보면, 수원에서는 31과 91초종, 전주는 19과 50초종, 그리고 부안에서는 32과 114초종이 발생되었다. 우점잡초로는 바랭이, 개망초, 흰명아주, 돌피, 깨풀, 닭의장풀 등이었다. 외래잡초는 44초종으로 전체의 28.8%를 점유하였으며, 개망초, 흰명아주, 미국 자리공, 망초 순으로 우점도가 높았다. 특히 외래잡초 중 개쑥갓은 미국, 캐나다, 독일 등에서 트리아진계 제초제 저항성 잡초로 일부 농가에서 비선택성 제초제인 글루포시 네이트암모늄액제에도 방제가 되지 않아 추가적인 연구가 필요하다. 발생한 잡초를 대상으로 PCA 공변량 분석을 한 결과, 뽕밭을 대표하는 잡초군락은 한련초 군락과 쇠별꽃 군락으로 유형화되었다. The weed flora in the mulberry fields were investigated in Suwon, Jeonju, and Buan in May, July, and September of 2014. The objectives of this study were to use the survey data for establishing weed control methods and to bring awareness of possible problematic weeds in the Korean mulberry fields. The survey was conducted in 53 regions, covering approximately <TEX>$145,925m^2$</TEX>. Altogether 153 weed species of 37 families were identified, of which 68 were annual, 39 species were biennial and 46 were perennial. The dominance was the highest with Digitaria ciliaris followed by Erigeron annuus, Chenopodium album, Echinochloa crus-galli var.crus-galli, Acalypha australis, Commelina communis etc. Exotic weeds presented 44 species with 28.8% of a total presence, of which Erigeron annuus was the highest, followed by Chenopodium album, Phytolacca americana, Conyza canadensis, Oxalis corymbosa etc. Especially, we should aware Senecio vulgaris, not controlled with glufosinate ammonium SL in the Korean mulberry fields because it was known as atrazine resistance in US, Canada, Germany etc. In the PCA plot, weeds presented in the mulberry fields were divided into two groups, Eclipta prostrata community and Stellaria aquatic community and weed flora of Suwon and Buan were different due to those only presented in Suwon.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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