Bibliographic record
Abstract
Stage 1 of the joint Canada-U.S. NEPTUNE seafloor observatory has been funded by the Canada Foundation for Innovation and the British Columbia Knowledge Development Fund with an overall budget of $62.4 million. The network is designed to provide as close to real−time data and images as possible to be distributed to the research community, government agencies, educational institutions and the public via the Internet. Covering much of the northern segment of the Juan de Fuca Plate, this first phase of the NEPTUNE project is scheduled to be installed, with an initial suite of ‘‘community experiments’’, in 2008. As part of the planning, NEPTUNE Canada held a series of three workshops to develop the science plans for these ‘‘community experiments’’; these experiments have a budget of approximately $13 million. The experiments will cover the gamut of oceanographic science themes including various aspects of: ocean climate and marine productivity, seabed environments and biological communities, fluids at ocean ridges, gas hydrates and fluids on continental margins, plate tectonics processes, associated earthquakes and tsunamis. The next three years will be spent developing and testing the necessary instrumentation for deployment on the network.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.009 |
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".