<i>The Production of Antibodies</i> (1941) by F. M. Burnet or by Burnet, Freeman, Jackson and Lush: Collaboration in research
Bibliographic record
Abstract
was published 84 years ago, in 1941. The authorship is normally attributed to Francis MacFarlane Burnet (1889-1985), 1960 Noble Laureate for his research on acquired immune tolerance and acknowledged as the most famous Australian scientist. A revised edition in 1949 was co-authored with Frank Fenner (1914-2010), another distinguished Australian virologist, best remembered for the elimination of smallpox in Australia and for control of the rabbit population. The curiosity and the topic of this paper is that three collaborators are listed on the title page of the 1941 book - Mavis Freeman, A. V. (Alan Vaughan) Jackson and Dora Lush. All three worked with Burnet at the Walter and Eliza Hall Institute in Melbourne between 1936 and 1939/1940 during which time they were co-authors on 25 research papers. Who were these collaborators, what did they contribute to the book and why the confusion over authorship? This journey takes us into research on influenza, poliomyelitis, smallpox, myxomatosis, herpes, Q fever and scrub typhus undertaken by brilliant scientists who contributed to important advances in virology and immunology with one tragic consequence.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".