Environmental indicators for sustainable beef cattle/forage production, case study for the south Interlake region of Manitoba
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
The federal government and the province of Manitoba are incorporating sustainable development and subsets of sustainable development including sustainable agriculture, into its political mandates. To monitor progress towards either sustainable development or agriculture, sustainability indicators are required. A subset of sustainability indicators includes environmental indicators. Environmental indicators are tools that can be used to monitor progress towards environmental sustainability. The goal of this project has been to determine if it is feasible to use environmental indicators for a specific agriculture practice, beef cattle/forage production. This was accomplished by identifying the environmental issues for this agriculture practice, reviewing available environmental indicators from various literature sources and compiling a list of environmental indicators for the agricultural practice. Data sets were located and researched to determine which could be used for the environmental indicators. Data sets were found for only three environmental indicators in the list Any other available data sets located were not specific enough to be used for environmental indicators for beef cattle/forage production. The data were collected on a land area basis, not a land development basis. (Abstract shortened by UMI.)
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) | 0.000 | 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