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A midnight coterie of transcendent fauna

2023· book-chapter· en· W4384939896 on OpenAlexaff
Asher D. Cutter

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAnthropoceneEnvironmental ethicsHumanityPaceHistoryEcologyGeographyPolitical scienceBiologyPhilosophyLaw

Abstract

fetched live from OpenAlex

Abstract Interweaves the prevailing themes from throughout the book in a forward-looking way. Considers the idea of entire communities of species shaped with the aid of genetic welding. Contrasts creation of new and extraordinary species in the Anthropocene with drastic environmental interventions like solar geoengineering to manage climate change. Revisits ideas about evolutionary engineering in the wild as domesticating nature, creating biological curiosities, and as a societal loss of innocence. Considers the weapons that animals have to defend themselves, including examples from jellyfish, poison birds, wasp stings, and pain-insensitive grasshopper mice. Concludes that humanity will continue to alter evolution’s path across our planet, while withholding advocacy for accelerating the pace of evolution with genetic welding, and promises that there is more change to come.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0350.009

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 head0.045
GPT teacher head0.326
Teacher spread0.281 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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