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Record W3113809285 · doi:10.14795/j.v7i4.569

GUARDING THE DANUBE AND BEYOND (I) COHORS II MATTIACORUM

2020· article· en· W3113809285 on OpenAlexaboutno aff
Costin Croitoru

Bibliographic record

VenueJournal of Ancient History and Archeology · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHistoriographyInterpretation (philosophy)Quarter (Canadian coin)Unit (ring theory)HistoryAncient historySpace (punctuation)Documentary evidenceAdministration (probate law)GenealogyClassicsArchaeologyGeographyPhilosophyLawPolitical scienceLinguisticsMathematics

Abstract

fetched live from OpenAlex

Organization and operation of the Danubian limes had been a concern of the Roman imperial administration for several centuries. The strategic conception for this space was translated into practice directly with the support of the Roman army. One of the early arrived units in the Lower Danube area was cohors II Mattiacorum; detachments of the unit would flank the river, being stationed in the “bridgehead” fortifications of Dinogetia and Barboși. The history of this auxiliary unit may be broadly restored pegged solely by epigraphic records which we shall review below, together with historiographical discussions related to the completion and interpretation of their text.Although many of the opinions mentioned below remain mere hypotheses until new archaeological discoveries are made, I believe based on the documentary material that we know now, that the evolution of the cohors II Mattiacorum can be reconstructed with some accuracy. Obviously, any new epigraphic find may confirm or “colour” what we know now. The unit’s development spans more than a century from the last quarter of the 1st century AD to the end of the 2nd century AD, leaving more consistent traces at Dinogetia and Barboși, Sexaginta Prista and Sostra. We know the names of some soldiers and unit commanders and the fact that the unit was transformed somewhere in the middle of its existence into a milliariaunit.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
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 head0.044
GPT teacher head0.217
Teacher spread0.172 · 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 designNot applicable
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

Citations1
Published2020
Admission routes1
Has abstractyes

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