Bibliographic record
Abstract
Abstract A new distribution map is provided for Puccinia sorghi Schw. Hosts: Maize ( Zea mays ). Information is given on the geographical distribution in AFRICA, Angola, Cameroon, Dahomey, Egypt, Ethiopia, Ghana, Ivory Coast, Kenya, Libya, Malagasy Republic, Malawi, Mauritius, Morocco, Mozambique, Nigeria, Réunion, Rhodesia, Sierra Leone, Somalia, South Africa, Sudan, Tanzania, Uganda, Zaire, Zambia, ASIA, Burma, Cambodia, China (Yunnan), (Kiangsu & Szechwan), Hong Kong, India (Bombay, Himachal Pradesh, Kashmir, Madras), (Bihar), (Mysore), Indonesia, Iran, Iraq, Israel, Japan (inc. Ryukyu Islands), Korea, Lebanon, Peninsular Malaysia, Nepal, Pakistan, Philippines, Saudi Arabia, Sri Lanka, Taiwan, Thailand, Turkey, USSR (Republic of Georgia), Yemen, AUSTRALASIA & OCEANIA, Australia (New South Wales), Fiji, New Caledonia, New Zealand, Norfolk Islands, Papua New Guinea, EUROPE, Austria, Britain (England & Wales), Bulgaria, Cyprus, Czechoslovakia, France, Germany, Greece, Hungary, Italy, Netherlands, Poland, Portugal (inc. Azores), Romania, Spain, Switzerland, USSR (Azerbaijan, Republic of Georgia, Lithuania) (Latvia) (Ukraine) (Kalashinkov), Yugoslavia, NORTH AMERICA, Canada, Mexico, USA (general), CENTRAL AMERICA & WEST INDIES, Belize, Costa Rica, Cuba, Dominican Republic, Guatemala, Haiti, Honduras, Jamaica, Nicaragua, Panama, Puerto Rico, Salvador, Trinidad, SOUTH AMERICA, Argentina (Tucumán), Bolivia, Brazil, Chile, Colombia, Ecuador, Guyana, Paraguay Peru, Surinam, Uruguay, Venezuela.
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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".