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The history of ocean resources: modeling cod biomass using historical records

2005· review· en· W2023350435 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2005
Typereview
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsFishingFisheryStock assessmentBiomass (ecology)PopulationMarine ecosystemEcosystemMarine conservationGeographyCommercial fishingIncentiveFisheries managementEcologyBiologyEconomics

Abstract

fetched live from OpenAlex

Managing the remnants of the ocean's resources is a critical issue worldwide, but evidence for what constitutes a healthy fish population remains controversial. Here, we use historical sources to understand ecosystem trends and establish a biomass estimate for a key marine species prior to the industrialization of fishing. Declining trajectories have been described for predatory fishes and complex coral reef systems globally, but few numerical estimates of past abundance exist. We combined historical research methods and population modeling to estimate the biomass of cod on Canada's Scotian Shelf in 1852. Mid 19th-century New England fishing logs offer geographically specific daily catch records, describing fleet activity on fishing grounds with negligible incentive to falsify records. Combined with ancillary fishery documents, these logs provide a solid, reliable basis for stock assessment. Based on these data we estimate a biomass for cod of 1.26 × 106 mt in 1852 – compared with less than 5 × 104 mt of total biomass today. In the current policy debate about rebuilding depleted fisheries and restoring marine ecosystems, it is important to recognize that fisheries for key commercial species like cod were far more productive in the past. As we attempt to rebuild these fisheries, our decisions should reflect real and realistic goals for management, not just recently observed catch levels.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.242
Teacher spread0.210 · 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