Bibliographic record
Abstract
Planning for artificial aquatic habitat development has typically occurred within the biological community. This paper traces the evolution of planning framework, and proposes the use of traditional urban and regional planning concepts in artificial aquatic habitat management. Aquatic habitat planning in the US as interpreted by states and regional fisheries commissions, exist merely at the project level and has not suitably evolved. A comprehensive systems framework is proposed which considers the role of onshore infrastructural support and offshore user and non-user considerations. The use of geographical information system (GIS) technology and its overall utility in planning and evaluation processes is discussed. A tradtional focus on exclusion or negative constraints represents only an initial set of considerations, but must be followed with an inclusive analysis which identifies intended sanctuary or human uses within marine habitat priority zones. Evaluation activities within habitat mangement are traditionally based on biological dynamics and are executed on a site by site basis. The need exists to demonstrate intended habitat and fishery management benefits on a state or regional basis. -from Author
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.003 |
| Insufficient payload (model declined to judge) | 0.989 | 0.989 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".