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Recalling Rome

2023· book-chapter· en· W4377037441 on OpenAlexaboutno aff
Joanna Story

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicHistorical and Religious Studies of Rome
Canadian institutionsnot available
Fundersnot available
KeywordsNinthArchbishopQueen (butterfly)Quarter (Canadian coin)ClassicsArtHistoryAncient historyArchaeology

Abstract

fetched live from OpenAlex

Abstract The chapter reviews the evidence for collections of verse inscriptions from Rome, known as syllogae, that circulated in Anglo-Saxon England and in Francia in the seventh, eighth, and ninth centuries, and discusses the ways in which these collections could act as itineraries for readers who had never travelled to Rome. It discusses the importance of inscriptions for imparting knowledge of the city of Rome and its churches, and as exemplars for verses for local buildings, and for reinforcing the importance of Rome in the minds of the faithful in distant places. Sylloges found in a manuscript written in Francia in the second quarter of the ninth century and later associated with Lorsch are analysed, especially the fourth Lorsch sylloge that records numerous inscriptions from St Peter’s, including one quoted by Hadrian in a letter to Charlemagne written in 793. Two epigrams in that collection are shown to have special resonance for Charlemagne and his queen, Hildegard, and can probably be dated to the king’s visits to Rome in 774 and 781. Another closely contemporary Frankish manuscript, made for Archbishop Arn of Salzburg, c.800, contains an itinerary of St Peter’s basilica concentrating on the oratories and transept on the south side. The itineraries contained in a similarly dated manuscript from Einseideln likewise reveal a contemporary Frankish vision of Rome.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0740.014

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 head0.059
GPT teacher head0.203
Teacher spread0.144 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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Same topicHistorical and Religious Studies of RomeFrench-language works237,207