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
Beef cattle is a product of great importance for the economy of countries like Brazil, nowadays the most important producer and exporter country of beef cattle in the world. However, to maintain itself on this important economic position, Brazil needs constantly to improve its production systems as well to invest in aspects related to sanitary control, according to the requirements of the consuming market like the European Community. The goal of OTAG project is to provide conditions to know the relative risks concerning to the bovine traceability, in the context of Southern Cone Countries and the EU policies. The project is based on the existing knowledge in Europe and Canada concerning to information systems and geo-decisional tools, as well to the interaction among experts and user groups from South Cone, Canada and Europe. OTAG prototype conceives the use of electronic devices for measuring the animal geo-localization in the herd. This information is associated to data about farm management, such as feeding and production systems in use. This paper presents the characteristics, tools and steps concerned to the development of the OTAG information system, aiming to obtain a prototype to analyse the beef cattle traceability under experimental conditions in Campo Grande, Brazil.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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