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Aratus and the Astronomical Tradition

2016· article· en· W4302329963 on OpenAlexvenueno aff
Emma Gee, John Ryan

Bibliographic record

VenueAestimatio Sources and Studies in the History of Science · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHistorical Astronomy and Related Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAstronomyPhilosophyArtPhysics

Abstract

fetched live from OpenAlex

Emma Gee takes up an ambitious task: an explanation of the lasting importance of the Phaenomena of Aratus, who transferred into Homeric verse a fourth century astronomical prose treatise of the same name by Eudoxus of Cnidus in the 270's bc.Fusing traditions of technical astronomy and meteorology with the didactic poetry of the Archaic poet Hesiod, the Phaenomena was an immediate classic and remained widely read and imitated for centuries to come.Although the poem has begun to receive more attention from scholars in the past 50 years, 1 a general study of its reception has yet to emerge.Gee seeks to fill this void by inserting the Phaenomena into a larger tradition of astronomical thought spanning the seven centuries between Plato and the Roman emperor Julian.Although Aratus' importance as a poet generally goes unchallenged, Gee's is the broadest treatment of the Phaenomena and its translations by Cicero, Germanicus Caesar, and Avienus as an astronomical tradition referenced at length by several important Latin poets.In the end, the success of the arguments relies on an intricate array of detailed, close readings of text, which compel to varying degrees.Even where these arguments fail to be completely convincing, versions of Gee's theses nonetheless remain plausible.Aratus and the Astronomical Tradition constitutes a large step in the general study of Aratus' ancient reception.In what follows, I will summarize and describe the arguments of each chapter, commenting on Gee's argumentative strategy along the way.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.010
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.246
Teacher spread0.220 · 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 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

Citations7
Published2016
Admission routes1
Has abstractyes

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