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Record W4415298735 · doi:10.1177/20530196251372132

Reproductive success in the anthropocene: A view through a One Health lens

2025· review· en· W4415298735 on OpenAlexafffund
Gabriela F. Mastromonaco, D.R. Bergfelt, L. Antonio González-Grajales, C J Lyons, Marcia de Almeida Monteiro Melo Ferraz

Bibliographic record

VenueThe Anthropocene Review · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenToronto Zoo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScope (computer science)BiodiversityReproductive healthReproductive successHuman healthEcosystem healthUnderpinningClimate change

Abstract

fetched live from OpenAlex

Over the past century, the increasing human impact on the planet's natural systems has been directly linked to the growing concern over biodiversity loss, and ultimately, human health. Reproduction, a critical factor underpinning species sustainability, is a complex and energetically demanding process that follows similar mechanisms across species. Further, it is one of the first biological functions to be altered in the event of ecosystem stress. The One Health paradigm, connecting humans, animals and plants to their environments, is a valuable framework for assessing the influence of anthropogenic changes on reproductive success across species. This review assesses the impacts of environmental pollution and climate change on the reproductive health of humans, animals and plants to better understand the broader scope of reproductive decline across the biodiversity spectrum, a fundamental step toward implementing One Reproductive Health objectives.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.202
GPT teacher head0.464
Teacher spread0.261 · 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
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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