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
Precision aquaculture is founded on a set of disparate, interconnected sensors deployed within the marine environment to monitor, analyze, interpret, and provide decision support for farm operations. Recent technological innovations facilitate aquaculture becoming part of the Internet of Things (IoT) - modern farms are characterized by hundreds of interconnected sensors that store and serve data, interact with other sensors and devices, and connect with a fog and cloud ecosystem. We describe the implementation of the precision aquaculture concept to a number of farms in eastern Canada. The work combines partners from industry, technology, and academia to provide data-driven insight and decision that promotes ecologically sustainable intensification of aquaculture. The article presents a first case study on how IoT can instrument, inform, and impact the aquaculture industry. Challenges related to connectivity, interoperability, and standardization are discussed, and we elucidate how our experiences can inform future activities.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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