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 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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.226 | 0.140 |
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".