Bibliographic record
Abstract
Distributed by Bullfrog Films, PO Box 149, Oley, PA 19547; 800-543-FROG (3764)Produced by Jed Riffe and Luke Griswold-TergisDirected by Luke Griswold-Tergis2022, Streaming, 100 mins This film concerns the scientific discovery by Russian scientist Sergey Zimov that melting arctic permafrost is threatening to release huge amounts of CO2 into the atmosphere, potentially creating a feedback loop that will lead to runaway climate change. “Impatient with world’s slow reaction to this news Zimov has single handedly begun a controversial plan to mitigate melting permafrost by reverse engineering the ‘Mammoth Steppe’ ecosystem – a now vanished ice age grassland, complete with Serengeti-like herds of roaming herbivores, which once stretched from Spain to Canada.” The film illustrates what one scientist can do to save our planet. Many people look at the words, climate change, and global warming like abstractions. If it doesn’t affect them directly in the immediate ‘now’, they show concern, but from a distance. Scientists from all over the world, including the United States come to witness and assist Zimoy to stave off this impending danger. To better understand what Zimoy is doing is to be steeped in the relationship of the natural world and our sustained impact on our planet. He is not creating a zoo but trying to save our planet for future generations. The permanence of frozen ground in the Arctic is no longer guaranteed as Earth’s temperatures continue to climb. But how much the degradation of so-called permafrost continues to be debated. In recent decades, permafrost has thawed, as Zimoy illustrates, because of global warming from heat trapped primarily by carbon dioxide released to the atmosphere from burning fossil fuels. Arctic warming is rising at twice the global average rate since 2000, according to the National Oceanic and Atmospheric Administration. As that increase accelerates the thaw of permafrost, the organic carbon contained within it breaks down and releases carbon dioxide, exacerbating climate change. While the film can at times, drag, this is an important documentary that will impact mankind for centuries to come if we do not act now. Awards:Adana Golden Boll Film Festival 2022 (Turkey); Anchorage International 2022 (Alaska); Architecture Film Festival Rotterdam 2022 (Netherlands); Banff Mountain Film Festival 2022 (Canada)
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.815 | 0.457 |
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".