Bibliographic record
Abstract
Abstract A new distribution map is provided for Liriomyza sativae Blanchard. Diptera: Agromyzidae. Hosts: Attacks a wide range of plants (primarily although not exclusively Fabaceae, Solanaceae and Asteraceae). Information is given on the geographical distribution in Europe (Finland, UK), Asia (China, Anhui, Fujian, Guangdong, Hainan, Hebei, Henan, Hunan, Shanxi, Sichuan, Zhejiang, India, Uttar Pradesh, Indonesia, Java, Iran, Israel, Japan, Honshu, Kyushu, Ryukyu Archipelago, Jordan, Malaysia, Peninsular Malaysia, Oman, Sri Lanka, Thailand, Turkey, Uzbekistan, Vietnam, Yemen), Africa (Cameroon, Nigeria, Sudan, Zimbabwe), North America (Canada, Ontario, Mexico, USA, Alabama, Arizona, Arkansas, California, Florida, Hawaii, Indiana, Louisiana, Maryland, New Jersey, Ohio, Pennsylvania, South Carolina, Tennessee, Texas), Central America and Caribbean (Antigua and Barbuda, Bahamas, Barbados, Costa Rica, Cuba, Dominica, Dominican Republic, Guadeloupe, Jamaica, Martinique, Montserrat, Netherlands Antilles, Nicaragua, Panama, Puerto Rico, St Kitts Nevis, St Lucia, St Vincent and the Grenadines, Trinidad and Tobago), South America (Argentina, Brazil, Ceara, Parana, Pernambuco, Rio de Janeiro, Rio Grande do Norte, Chile, Colombia, French Guiana, Peru, Venezuela), and Oceania (American Samoa, Cook Islands, Federal States of Micronesia, French Polynesia, Guam, New Caledonia, Northern Mariana Islands, Samoa, Vanuatu).
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".