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Record W2143379293 · doi:10.1111/fog.12007

Setting the record straight on drivers of changing ecosystem states

2012· article· en· W2143379293 on OpenAlexaff
Kenneth T. Frank, Brian Petrie, Jonathan A. D. Fisher, William C. Leggett

Bibliographic record

VenueFisheries Oceanography · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsQueen's UniversityMemorial University of NewfoundlandBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsTrophic levelEcosystemOceanographyForcing (mathematics)Argument (complex analysis)EcologyContinental shelfPredationMarine ecosystemTrophic cascadeClimate changeEnvironmental scienceGeographyGeologyClimatologyBiologyFood web

Abstract

fetched live from OpenAlex

Abstract This short communication is a response to the critique by Greene (2012), who puts forward the argument that the dynamics of northwest A tlantic continental shelf ecosystems are strongly influenced by changes in A rctic climate, as indexed by surface salinity. The argument, in its essence, discounts any indirect effects from over‐exploitation of top predators on lower trophic levels in northwest A tlantic ecosystems. Frank et al . ( Science 308 , 2005, 1621; Nature 477 , 2011, 86) reported the existence of cascading trophic interactions with particular emphasis on the eastern S cotian S helf. Greene argues that the events occurring in the G ulf of M aine/ G eorges B ank region are representative of all N orthwest A tlantic shelf systems, despite previous research (Frank et al. Trends Ecol. Evol . 22 , 2007, 236; Petrie et al. Fish. Oceanogr . 18 , 2009, 83) that has shown a differential pattern of forcing ranging from top‐down in species‐poor, cold water systems to bottom‐up in warmer, more species‐rich systems, including G eorges B ank.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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 designObservational
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

Citations7
Published2012
Admission routes1
Has abstractyes

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