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Mechanics from Aristotle to Einstein

2015· article· en· W606275291 on OpenAlexvenueno aff
Michael J. Crowe, Peter Machamer

Bibliographic record

VenueAestimatio Sources and Studies in the History of Science · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRelativity and Gravitational Theory
Canadian institutionsnot available
Fundersnot available
KeywordsEinsteinGalileo (satellite navigation)EpistemologyPhilosophyCivilizationTheoretical physicsPhysicsHistoryClassical mechanics

Abstract

fetched live from OpenAlex

In a remarkably concise compass, Crowe presents, through actual examples, the fascinating story of how philosophers and scientists through the ages have tried to understand how things move. Included are substantial selections from the writings of Aristotle, Oresme, Descartes, Galileo, Huygens, Newton, and Einstein. The selections are furnished with extensive notes aimed at guiding nonspecialist readers through the texts. Introductory sections provide historical information that helps us understand and appreciate each chapter in the story, which Crowe aptly characterizes as the most remarkable story in all secular history. At the same time, Mechanics from Aristotle to Einstein is itself an introduction to the foundations of mechanics. Examples and problems are provided to give a true hands on experience of these ideas and discoveries, which are fundamental to an understanding of both our physical universe and our civilization itself. This title is the winner of the Choice Outstanding Academic Title award, 2009.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0030.005
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.003

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 head0.087
GPT teacher head0.315
Teacher spread0.228 · 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.

Study designTheoretical or conceptual
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

Citations12
Published2015
Admission routes1
Has abstractyes

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