Bibliographic record
Abstract
Distributed by Collective Eye Films, 1315 SE 20th Ave. #3, Portland OR 97214; 971-236-2056Produced by David Gross, Jo-Anne McGowan, Sarah Noonan, and Jennifer PeedomDirected by Gisela Kaufmann and Joseph Nizeti2023, Streaming, 40 mins Fungi: Web of Life is a fascinating and visually stunning documentary about fungi. The documentary provides a broad look at how fungi are connected to other organisms and the important ecological role fungi play in the environment. Fungi: Web of Life uses a voice-over narration by Björk and also features biologist Merlin Sheldrake on screen and via voice-over. Sheldrake is a popular science writer and fungi researcher who guides viewers through much of the film, introducing viewers to the Fungarium in Kew Gardens, the largest collection of fungi samples, and guides viewers through the Tarkine rainforest in Tasmania. The other primary focuses of the film are a group of fungal researchers in Yunnan, China led by Peter Mortimer, and a company, Ecovative Designs, that develops materials made out of mycelium. Each viewpoint is used to illustrate the central theme of the importance of fungi in the ecosystem and the potential of fungi to address issues facing humanity. The film also emphasizes how much scientists are still learning about fungi and its possible utilities. The highlight of Fungi: Web of Life is the stunning cinematography. It is filled with fascinating time-lapses of fungi growth and gorgeous landscapes. The time lapse photography is a particularly compelling way to look at fungi and it shows a view of fungi that will be new to many viewers. As a short documentary, there is not enough time to delve more deeply into these fascinating topics. As a result, the film provides mostly surface level overview, and it might not have the depth of information needed in a university setting; it would be most appropriate for a high school setting. Additionally, the film focuses on the importance of fungi on a larger scale and does not cover fungi at the organism or classification level. Viewers looking for academic information about fungi biology, classification or life cycles would be better served looking for more academic films. However, it would be a good introduction to fungi and some segments may be useful in specific university courses. Discussion of the role of fungi in the environment could be useful in ecology classes and explorations of fungi to make materials would be useful in applied science courses or engineering. Overall, Fungi: Web of Life is a well-crafted and compelling film that would be enjoyed by any audience. Awards:Best Cinamatography and Best Voice Over Cast (GeekFest Toronto); Best Eco Documentary (San Pedro International Festival); Best Educational Media (Raw Science Film Festival); Scientific Merit (SCINEMA International Film festival)
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.581 | 0.411 |
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".