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Record W4300582561 · doi:10.47886/9781934874301.ch17

Advancing an Ecosystem Approach in the Gulf of Maine

2012· book-chapter· en· W4300582561 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2012
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsScrutinyOverfishingEcosystemMarine conservationEnvironmental resource managementGeographyMarine ecosystemPolitical scienceEcologyEnvironmental scienceFishing

Abstract

fetched live from OpenAlex

Abstract .—The goal of this session was to provide a synthesis of the major pressures being exerted on the Gulf of Maine (GOM), including the Bay of Fundy, that constrain the achievement of ecosystem objectives or the desired state of valued attributes (ecological, social/cultural, and economic). The GOM boasts a diverse ecosystem, much changed ecologically over the past 400 years and long the subject of intense scrutiny by a host of universities, marine labs, and research centers in both the United States and Canada. While the presentations in the session noted that this ecosystem must cope with stressors that range from climate change to pharmaceuticals and nutrient loading to overfishing, the presentations also presented an historical perspective with lessons for resiliency, including successes of finer-scale and spatial management as well as collaborations in research and communication. It was recognized that a concerted effort to raise environmental literacy amongst the gulf ’s residents is essential to ensure that the full value of its ecosystems and resources is recognized and protected for future generations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.229
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2012
Admission routes1
Has abstractyes

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