Bibliographic record
Abstract
Returning, still rather hungry and footsore, to New Zealand and Victoria University, I spent the rest of 1959, like Peter, working on my MSc thesis. Our theses consisted of joint manuscripts and one solo effort each. Peter worked up the sedimentology of the Beacon Sandstone strata and I fear I insulted the mineralogy of the Ferrar Dolerite sills. (It was my one and only foray into igneous mineralogy and is now properly lost and forgotten.) I was busy the whole year, but after the action and excitement of VUWAE 2, felt somewhat unsettled. Then in late November Bob Clark received a cable asking if he had a candidate suitable for a research assistantship in Geology at the University of New England in New South Wales. The position would allow study for a PhD. Although the New Zealand Geological Survey had offered me a position in sedimentary petrology upon completion of the MSc, the chalice of an Australian adventure with a bonus PhD candidature proved irresistible. I obtained leave of absence from the Survey, which could perhaps see two advantages: I might learn something about sedimentary petrology in the course of the PhD and, probably more importantly, they would benefit by a two- to three-year salary saving. In July 1960 I took up tile assistantship at the University of New England, a charming rural campus situated at about 1000 metres altitude atop the New England Tablelands. Rural research was much emphasized and because of the University's farms and extensive campus, it claimed to run about a student to the acre (fewer during droughts). Signing me onto the staff the Registrar apologized for the smallness of my salary. I didn't tell him it was £50 more than my Survey position in New Zealand.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.289 | 0.111 |
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".