United Nations IPCC Climate Alarmists Discredited Yet Again Propaganda Disguised as Science and Sold by Supporters of Climate Change
Bibliographic record
Abstract
The United Nations IPCC has been caught again trying to pass off propaganda from environmental activists and vested interests as being “scientific research ” (1, 2, 3). According to Gunter (2): “Canadian researcher Steve McIntyre discovered earlier this week that the IPCC’s recent report on alternative energy — which asserted that it was possible to convert the world to 80 % green energy by 2050 if politicians would simply tax conventional sources and spend billions on alternative sources — was lifted largely from Greenpeace reports. The lead author of the IPCC report turns out to be Sven Teske, a Greenpeace climate and energy campaigner, who the IPCC does not identify as such in either the report or its media releases. Mr. Teske is also the author of much of the Greenpeace material on which the IPCC report is based, in effect making him a peer reviewer of the validity of his own material. Imagine the reaction, for instance, if a government had produced a fossil-fuel friendly report based on work by an oil sands engineer, without revealing the source, and had paid the same engineer to write its own summary of his initial work. That is what the IPCC has stooped to in this case and it eliminates any credibility the organization had left on the climate file.”
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".