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Record W2290176395 · doi:10.5281/zenodo.27700

0-D Bioeconomic Marine Trophic Size-Spectrum (Boats) Model (Review Version)

2015· dataset· en· W2290176395 on OpenAlexaff
David A. Carozza, Daniele Bianchi, Eric D. Galbraith

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2015
Typedataset
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMcGill University
Fundersnot available
KeywordsTrophic levelEnvironmental scienceOceanographyFisheryEcologyBiologyGeology

Abstract

fetched live from OpenAlex

This is version 1.0 of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, a bioenergetically-constrained coupled fisheries-economics model for global studies of harvesting and climate change. The code is written in MATLAB version R2012a. This release contains the zero-dimensional version of the code that models a single oceanic grid cell. This release is part of the peer review for the journal Geoscientific Model Development, which was published as Carozza et al. (2016) [Carozza, D. A., Bianchi, D., and Galbraith, E. D.: The ecological module of BOATS-1.0: a bioenergetically constrained model of marine upper trophic levels suitable for studies of fisheries and ocean biogeochemistry, Geosci. Model Dev., 9, 1545-1565, doi:10.5194/gmd-9-1545-2016, 2016.].

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.045
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0450.046

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 head0.029
GPT teacher head0.238
Teacher spread0.209 · 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 designSimulation or modeling
Domainnot available
GenreDataset

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

Citations1
Published2015
Admission routes1
Has abstractyes

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