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Record W7098191567

EXECUTIVE SUMMARY

2010· article· en· W7098191567 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicPaleopathology and ancient diseases
Canadian institutionsnot available
Fundersnot available
KeywordsSound (geography)ShoreEcosystemExecutive summaryEstuaryEcosystem healthRestoration ecologyEcosystem servicesCoastal management
DOInot available

Abstract

fetched live from OpenAlex

(WDFW) co-lead an ecosystem study of the Puget Sound called the Puget Sound Nearshore Ecosystem Restoration Project (PSNERP). The study commenced in federal Fiscal Year (FY) 2001 and is scheduled to conclude in FY 2012. The purpose of the study is to evaluate significant ecosystem degradation in the Puget Sound Basin; to formulate, evaluate, and screen potential solutions to these problems; and to recommend a series of actions and projects to restore and preserve critical nearshore habitat. The second phase of work, which will entail implementing process-based restoration projects, will commence when the study is completed and federal and state restoration funds are dedicated for necessary projects. These projects will be carried out to improve the integrity and resilience of ecosystem processes and to promote environmental and human health and well being. The geographical domain of the study area extends along 2,500 miles of shoreline from the Canadian border, through Puget Sound, and along the Strait of Juan de Fuca to Cape Flattery. PSNERP defines the nearshore as the area that extends from the top of shoreline bluffs or upstream in estuaries to the head of tidal influence waterward to the deepest extent of the photic zone. The protection and restoration of nearshore habitats in Puget Sound requires the application of recovery actions or “management measures ” that address nearshore ecosystem processes, functions, and structures.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.995

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.018
GPT teacher head0.225
Teacher spread0.207 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2010
Admission routes1
Has abstractyes

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