MétaCan
Menu
Back to cohort

First inventory of marine debris on Alegranza, an uninhabited island in the Northeast Atlantic

2022· article· en· W4220803265 on OpenAlexaboutno aff
Alicia Herrera, J. Alexis Rivera, Teresa Moreno, Ico Martínez, May Gómez

Bibliographic record

VenueMarine Pollution Bulletin · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
FundersMinisterio para la Transición Ecológica y el Reto Demográfico
KeywordsDebrisMarine debrisArchipelagoOceanographyGeographyArchaeologyLicenseFisheryGeology

Abstract

fetched live from OpenAlex

Alegranza is the most northerly island of the Canary Islands archipelago, the first obstacle crossed by the Canary Current. From July to October 2020, six expeditions were led to the island to make a first inventory of marine debris and its possible source and origin. In total, 3667 objects weighing 321 kg were removed, excluding wooden objects. Of these, 97.7% were plastics, the most abundant being drink bottles (25.4%). While knowing the origin, source and pathway of debris is difficult, legible labels provided valuable information. In Alegranza, 66.7% of the legible bottle labels indicated Asian countries of manufacture, which is evidence that the source is maritime traffic in the region. The lobster trap license labels from the east coast of the United States and Canada were dated from 1999 to 2018, supporting both the exogenous origin and long lifetime in the ocean of these debris.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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 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

Citations14
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMarine Pollution BulletinSame topicMicroplastics and Plastic PollutionFrench-language works237,207