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Elemental cycles

2011· book-chapter· en· W646752220 on OpenAlexaff
John King

Bibliographic record

VenueCambridge University Press eBooks · 2011
Typebook-chapter
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

INTRODUCTION For nearly all of its four and a half billion years of existence, the Earth's environment has followed a path and pace of change affected much less by human activities than by other, much larger, natural forces. Humans began having an impact a few thousand years ago through such activities as the slash and burn gardens in the tropics and the burning of grasslands by hunter/gatherer societies prior to forest clearing for agriculture in temperate regions. In the past few hundred years, however, burgeoning human populations and their activities in all parts of the globe have greatly increased the scale of impact. The goal of this chapter is to examine the period prior to the advent of widespread human effects on the Earth's environment, especially factors important to plants and the roles they play in the biosphere. For the first half billion years or so after it began forming, the Earth was shaped and reshaped by physical and chemical forces alone. Around 3.8 billion years before the present (BP), the outer crust , which formed as the Earth cooled sufficiently to form a solid, unbroken surface layer, cracked into a number of massive plates floating on a deeper mantle of molten rock. Ever since, these tectonic plates on which the continents are carried have continued to move from place to place at the Earth's surface and, at their edges, to sink beneath one another into the hot mantle below, a process called subduction .

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.046
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0460.011

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 head0.015
GPT teacher head0.162
Teacher spread0.147 · 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 designTheoretical or conceptual
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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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