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Record W2939482862 · doi:10.1177/0309133319832607

A formal Anthropocene is compatible with but distinct from its diachronous anthropogenic counterparts: a response to W.F. Ruddiman’s ‘three flaws in defining a formal Anthropocene’

2019· article· en· W2939482862 on OpenAlexaff
Jan Zalasiewicz, Colin N. Waters, Martin J. Head, Clément Poirier, Colin Summerhayes, Reinhold Leinfelder, Jacques Grinevald, Will Steffen, P. K. Haff, John McNeill, Michael Wagreich, Ian J. Fairchild, Daniel D. Richter, Davor Vidas, Mark Williams, Anthony D. Barnosky, Alejandro Cearreta

Bibliographic record

VenueProgress in Physical Geography Earth and Environment · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsBrock University
Fundersnot available
KeywordsAnthropoceneDiachronousChronostratigraphyHoloceneGeologyPaleontologyEarth scienceSedimentary rockTectonics

Abstract

fetched live from OpenAlex

We analyse the ‘three flaws’ to potentially defining a formal Anthropocene geological time unit as advanced by Ruddiman (2018). (1) We recognize a long record of pre-industrial human impacts, but note that these increased in relative magnitude slowly and were strongly time-transgressive by comparison with the extraordinarily rapid, novel and near-globally synchronous changes of post-industrial time. (2) The rules of stratigraphic nomenclature do not ‘reject’ pre-industrial anthropogenic signals – these have long been a key characteristic and distinguishing feature of the Holocene. (3) In contrast to the contention that classical chronostratigraphy is now widely ignored by scientists, it remains vital and widely used in unambiguously defining geological time units and is an indispensable part of the Earth sciences. A mounting body of evidence indicates that the Anthropocene, considered as a precisely defined geological time unit that begins in the mid-20th century, is sharply distinct from the Holocene.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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 teacher head, not a consensus.

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

Citations53
Published2019
Admission routes1
Has abstractyes

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