Report on the Marine Imaging Workshop 2017
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
Marine optical imaging has become a major assessment tool in science, policy and public understanding of our seas and oceans. Methodology in this field is developing rapidly, including hardware, software and the ways of their application. The aim of the Marine Imaging Workshop (MIW) is to bring together academics, research scientists and engineers, as well as industrial partners to discuss these developments, along with applications, challenges and future directions. The first MIW was held in Southampton, UK in April 2014.\n\nThe second MIW, held in Kiel, Germany, in 2017 involved more than 100 attendees, who shared the latest developments in marine imaging through a combination of traditional oral and poster presentations, interactive sessions and focused discussion sessions. This article summarises the topics addressed during the workshop, particularly the outcomes of these discussion sessions for future reference and to make the workshop results available to the open public.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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