An Arctic Marine Ecosystem Conceptual Model: The Interactions Matrix Revealed
Bibliographic record
Abstract
In November 2016, the US Bureau of Ocean Energy Management, Office of Naval Research, and National Science Foundation supported a workshop to create a unifying pan-Arctic conceptual model of the current state and future changes of the Arctic Marine Ecosystem (AME). One component of this conceptual model is a matrix of interactions that determine the functioning of the AME. This matrix was developed using a parsimonious list of Key Elements, distributed between five categories: Atmosphere, Land-Ocean/Shelf-Interior Connections, Physical Environment, Biology, and Human Impacts. To determine the strength and direction of connections between Key Elements, direct interactions were characterized in a matrix array by evaluating directionality, relative magnitude, and scientific (un)certainty. Indirect interactions were removed, because these should be captured by chains of direct interactions. In this poster participants can explore connections between Key Elements through an interactive platform. With this participatory presentation we hope to elicit feedback, comments, and criticisms of the interactions presented, including their magnitude and the direction of their effects now and into the future. Discussion generated during this presentation will be used to refine the matrix.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".