MétaCan
Menu
Back to cohort
Record W2503358427 · doi:10.1093/0195168755.001.0001

Transforming the Twentieth Century: Volume 2: Technical Innovations and Their Consequences

2006· book· en· W2503358427 on OpenAlexaff
Vaclav Smil

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsConsumption (sociology)EngineeringCivilizationElectricityIndustrial RevolutionManufacturing engineeringEconomyBusinessPolitical scienceEconomicsElectrical engineeringLawSociologySocial science

Abstract

fetched live from OpenAlex

Abstract This book is a systematic interdisciplinary account of two epochal trends: the history of the 20th century’s technical transformation based on the unprecedented surge of innovation that took place in Europe and North America during the three pre-WWI generation (1867-1914); and the history of new fundamental inventions during the period 1914-2000. Mass consumption of fossil fuels provided the energetic foundation of this progress. New ways of making steel — the leading metal of our civilization — and new materials including plastics and silicon, opened entirely new technical possibilities. Rationalized production, be it in agriculture or manufacturing, benefited from advancing mechanization, automation, and robotization. New epochal inventions included the discovery of nuclear fission, followed by the rapid development of nuclear weapons and commercial generation of nuclear electricity; the discovery of gas turbines (and their use in jet airplanes as well as in stationary applications); and the invention of solid-state electronics based on semiconductors used to make transistors, integrated circuits, and microprocessors, the key components of modern computing. The new economy based on unprecedented levels of energy consumption brought not only mass consumption and higher quality of life, but also some worrisome social problems and environmental changes; its prospects remain uncertain.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.623
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.202
Teacher spread0.176 · 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.

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".

Quick stats

Citations21
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicEconomic Growth and ProductivityFrench-language works237,207