319 Reflections on the most cited paper in the ninety-nine-year history of Canadian Society of Animal Science
Bibliographic record
Abstract
Abstract Measurement of nutrient digestibility is a key pillar in estimating the value of feeds for livestock. Conditions are not always amendable to estimating feed digestibility through total collection methods, and as a result digestibility markers are frequently employed. The first “Digestibility markers” were reported in the early 1900s where colored glass beads were used to estimate the flow of digesta through the digestive tract. Subsequently, a myriad of digestibility markers has been assessed with the internal markers; acid insoluble ash, acid detergent lignin, indigestible neutral detergent fiber and n-alkanes and the external markers titanium dioxide and chromic oxide being the most common. Chromic oxide (Cr2O3) was first proposed as a digestibility maker in 1918 and continues to be widely used in modern day metabolism, confined performance and grazing livestock experiments. It was the demand to use chromic acid as a digestibility marker that led Terry and Mira Fenton to publish the article “An improved procedure for the determination of chromic oxide in feed and feces” in the Canadian Journal of Animal Science in 1979. This became the most cited article in the history of the journal with over 800 citations. The procedure eliminated the use of nitric acid in a pre-digestion step and ashing reduced the organic matter content, making it less likely that perchloric acid would be converted to anhydrous perchloric acid which poses an explosive hazard. The procedure continues to be widely used to measure Cr2O3 as a digestibility marker and has made a significant contribution to our assessment of the value of a wide range of feeds for Canadian livestock.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.079 | 0.045 |
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".