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Record W2659362582 · doi:10.1101/154526

Mammal extinctions and the increasing isolation of humans on the tree of life

2017· preprint· en· W2659362582 on OpenAlexaff
Sandrine Pavoine, Michael B. Bonsall, T. Jonathan Davies, Shelly Masi

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsMcGill University
Fundersnot available
KeywordsHomo sapiensTree of life (biology)BiodiversityExtinction (optical mineralogy)Extinction eventOptimal distinctiveness theoryMammalEcosystemBiologyEcologyEvolutionary biologyEnvironmental ethicsGeographyPhylogenetic treePsychologyPaleontologySociologySocial psychology

Abstract

fetched live from OpenAlex

Abstract A sixth great mass extinction is ongoing due to the direct and indirect effects of human pressures. However, not all lineages are impacted equally. As humans, we frequently believe that we hold a unique place on Earth. Here, we show that our current impacts on the natural world risk to heighten that expectation. Evolutionary proximity to Homo sapiens emerges as a powerful predictor of extinction risk among mammals. Our analysis shows that the species most closely related to H. sapiens are exposed to a large variety of threat types and that they may also have greater intrinsic sensitivity to threats. Pruning back the tree of life around us will lead to our species being among those with the fewest close relatives. We will erase our evolutionary history, forcing its uniqueness. If no action is taken, we will lose crucial biodiversity for the preservation of Earth ecosystems, and a key reference to what makes us human.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.034
GPT teacher head0.274
Teacher spread0.240 · 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
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

Citations2
Published2017
Admission routes1
Has abstractyes

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