Bibliographic record
Abstract
As mentioned in our last newsletter, the Friends were supporting professors Barry Cooper of the University of Calgary, and Tim Patterson of the Carleton University in their endeavours to hold a meeting of scientists. The scientists held a spectrum of opinion with respect to climate change. We viewed it as a beginning of a dialogue which could grow into a national debate as to the causes for our warming climate. The meeting was to be held in Ottawa on September 20, 2007. The University of Calgary in early September unexpectedly cancelled its support of the meeting which had to be subsequently postponed for an indefinite period. The Friends organized a successful breakfast meeting on Friday September 14 which was sponsored by six well known business leaders. Dr. Ross McKitrick, associate Professor of Economics, University of Guelph, gave a presentation in which he argued for a carbon tax linked to real changes in atmospheric temperature. He explained why a carbon tax linked to mean observed atmospheric temperature changes should appeal to both sides of the global warming debate. There appeared to be general agreement among attendees that the idea was a logical response which would not gamble in advance as to which side of the debate was correct and that it warranted further investigation. For further information about Dr. McKitricks proposal please
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.157 | 0.107 |
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".