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
Despite recognition that non-native plant species represent a substantial risk to natural systems, there is currently no compilation of weeds that impact on the biodiversity of the rangelands within Australia. Using published and expert knowledge, this paper presents a list of 622 non-native naturalised species known to occur within the rangelands. Of these, 160 species (26%) are considered a current threat to rangeland biodiversity. Most of these plant species have been deliberately introduced for forage or other commercial use (e.g. nursery trade). Among growth forms, shrubs and perennial grasses comprise over 50% of species that pose the greatest risk to rangeland biodiversity. We identify regions within the rangelands containing both high biodiversity values and a high proportion of weeds and recommend these areas as priorities for weed management. Finally, we examine the resources available for weed detection and identification since detecting weeds in the early stages of invasion is the most cost effective method of reducing further impact.
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 | 0.000 | 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) | 0.001 | 0.000 |
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