Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past several decades, with the introduction of ecology as a scientific pursuit, China has made advancements in ensuring the health and sustainability of its forests and biodiversity. A very large number of endemic plant and vertebrate species are found in China, plenty of which have value in many areas, including aesthetics and medicine. China’s biodiversity faces many threats, including the invasion of alien species, urbanization and deforestation, as well as global warming. As the monetary value of the products obtained from the many endemic species has been recognized, an increase in environmental awareness has surfaced. Several domestic and international environmental non-governmental organizations (ENGOs) committed to the preservation of China’s forests and wildlife have played an increasing role in educating both the Chinese and the rest of the world. The major issue concerning the preservation of China’s biodiversity is a lack of education in the biological sciences. Increased funding to attract more educated people to work in the Ministry of the Environment, as well as to aid in educating more people is the first logical step.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 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 it