ABS volume 4 issue 2 Cover and Back matter
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
Enteric methane emission from ruminants contributes substantially to the greenhouse effect. Few studies have focused on the genetic variation in enteric methane emission from dairy cattle. One reason for that is the limited<br/>number of methods appropriate for large scale phenotyping to measure a sufficient number of animals available to estimation of additive genetic variance. A method to measure methane in dairy cattle using a Fourier Transformed Infrared (FTIR) approach during milking in Automatic milking systems was implemented by Lassen et al . (2012). Such data showed repeatability estimates around 0.40 for the ratio between methane and carbon dioxide concentrations. Using the ratio between methane and carbon dioxide as a phenotype makes it possible to quantify the amount of methane produced<br/>per cow, because the amount of carbon dioxide can be estimated from variables such as weight, milk production and feed intake (Madsen et al<br/>., 2010). In a study of 548 heifers a heritability estimate of 0.35 was obtained for predicted methane emission based on registrations on feed intake rather than on direct measurements (de Haas et al., 2011). Estimates of this<br/>magnitude justify the use of genetic tools to reduce methane emission from dairy cattle. Another study (Wall et al ., 2010) has shown that selecting for correlated indicator traits such as productivity and efficiency would help lowering the methane emission from the cattle production. Furthermore, it is still important to have emphasis on production traits through use of a<br/>total merit indexes to avoid a decline in economically important traits when reducing methane emission. However, key genetic parameters are still inaccurate and would therefore benefit from being re-estimated on larger numbers of animals and records based on reliable direct methods. The objective of this study was to estimate the heritability for enteric methane<br/>emission from Danish Holstein cows using a non-invasive method
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.131 | 0.287 |
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