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Record W3192622167 · doi:10.1016/0967-0653(95)91021-u

10.1016/0967-0653(95)91021-u

2000· article· en· W3192622167 on OpenAlexvenueno aff
William R. Gordon

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeographic information systemHabitatGeographyEnvironmental resource managementInformation systemEnvironmental planningEcologyRemote sensingEnvironmental scienceBiologyEngineering

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.626
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)1.0000.999

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.

Opus teacher head0.004
GPT teacher head0.148
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations16
Published2000
Admission routes1
Has abstractyes

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