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Record W7054779616

Appunti su metis e tragedia. L'Elettra di Sofocle

2022· article· en· W7054779616 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2022
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodDiafiltrationTSG101DysgeusiaFusible alloyLiquationProteogenomicsDemotion
DOInot available

Abstract

fetched live from OpenAlex

This paper is part of a larger research project on the notion of μῆτις in Greek tragedy and seeks to stress the significance of this idea in the analysis of Sophocles’ Electra, with specific attention to the play’s intertextual relationship with Homeric poetry. It will focus, in particular, on the prologue (where Orestes’ Odyssean character is introduced), on the controversial rhesis on Orestes’ false death (modelled on Antilochus’ race in Iliad 23), as well as on the recognition scene of Orestes and Electra, where the contrast between the different heroic identities of the two characters becomes evident

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.045

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 studies0.0030.004
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.037
GPT teacher head0.299
Teacher spread0.262 · 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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