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Record W1538197899 · doi:10.5772/27704

Connectivity as a Management Tool for Coastal Ecosystems in Changing Oceans

2012· book-chapter· en· W1538197899 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOceanography · 2012
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsMcGill UniversityUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEcosystemEnvironmental resource managementMarine ecosystemOceanographyEnvironmental scienceGeographyGeologyEcologyBiology

Abstract

fetched live from OpenAlex

Recent theoretical management research has focused on systems from species to ecosystem at large scales (i.e., metapopulations and meta-ecosystems), and the links between habitats patches and subpopulations are of crucial importance to understand, predict, and manage resource dynamics. One of the key characteristics affecting the dynamics and demography of metapopulations is thus connectivity (Hanski, 1999; Kritzer & Sale, 2004; Moilanen & Nieminen, 2002), the exchange or flux of material between different locations (Cowen & Sponaugle, 2009). Because of its broad definition and growing relevance, “connectivity” is now employed in a number of fields, including metapopulation ecology. Consequently, several definitions of connectivity exist with the main differences between them lying in the spatial scale of study (Kadoya, 2009). In this review, we consider connectivity in its broadest sense of demographic or population connectivity: the exchange of individuals among geographically separated subpopulations in a metapopulation (Cowen & Sponaugle, 2009).

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.196
Teacher spread0.183 · 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