Bibliographic record
Abstract
It was April 11, 2014, and the McGill University press release went online at 1:30 in the afternoon. Although I’d published many articles, they were on fundamental geoscience; the release summarized the first one that had significant social and political consequences. Its title, “Scaling Fluctuation Analysis and Statistical Hypothesis Testing of Anthropogenic Warming,” was arcane, but the release was clear enough: “Statistical analysis rules out natural- warming hypothesis with more than 99% certainty” (the article, published in Climate Dynamics, is hereafter referred to as CD). It had been fifteen months since the original submission went to peer review, but now the pace picked up dramatically. Within hours, the tone was set by the skeptic majordomo Viscount Christopher Monckton of Brenchely, who displayed his Oxbridge classics erudition by deliciously qualifying the paper as a “mephitically ectoplasmic emanation from the Forces of Darkness.” Three days later, with the release getting 12,000 hits per day, the “Friends of Science” sent an aggressive missive to the McGill chancellor asking that it be removed from McGill’s site. The Calgary- based group with its Orwellian name was set up in 2002 to promote the theory that “The sun is the driver of climate change. Not you. Not CO2.” (Fig. 6.1). One could understand their thunder. Rather than trying to prove that the warming was anthropogenic— something that is impossible to do “beyond reasonable doubt”— the new paper closed the debate2 by doing something far simpler: by disproving the “Friends” Giant Natural Fluctuation (GNF) hypothesis. If we exclude either divine or extraterrestrial intervention, then the warming is natural or it is human; there is no third alternative. The skeptics were stuck. To add insult to injury, their prepackaged sermons on the inadequacies of computer models or their speculations about solar variability were irrelevant. Provoked by the media attention and several Op- Eds in the hours, days, and weeks that followed, in email, blogs, and Twitter, I was treated to a deluge of abuse: “atheist,” “Marxist,” “hippy name,” and so on— everything, it seemed, short of death threats.
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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.097 | 0.048 |
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".