Impacts of the CSIRO climate modelling program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The role of climate modelling groups in the development of international agreements that aim to assess future climatic risks and limit greenhouse gas concentrations is not well recognised. It is arguable that no such agreements would have been possible without carefully designed and managed research programs that provided the data upon which these risks and thus, decisions were made. Many groups contributed data that underpinned the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report published in 2014 that led to the ground-breaking Paris Agreement. Australia’s contribution included the results of a CSIRO climate model which had its genesis in a relatively simple weather forecast model two decades previously. Two people were mainly responsible for the modelling program which led to this accomplishment—Barrie Hunt and Hal Gordon. A brief history of the program is described here and. Examining some basic metrics reveals some surprising impacts.
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it