MétaCan
Menu
Back to cohort
Record W7045770650

Byzantine navy and piracy during emperor Michaels VIII Paleologus (1261-1282)

2011· article· en· W7045770650 on OpenAlexaboutno aff

Bibliographic record

VenueElectronic Archive of Ural Federal University (ELAR UrFU) · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsByzantine architectureEmperorNavyCommissionQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

After getting Constantinople back the emperor Michael VIII Palaeologus created powerful navy to ensure the defense of the Empire. Development of the navy made the recruitment necessary. The first Byzantine crews were formed with Gasmuli (descendants of cross marriages between the Byzantines and the Latin’s). The Byzantine navy was very successful in battles with Venetians, who suffered from the Greek pirates attacks. The last quarter of the XIII century was the time for the rise of the Greek sea robbery. The main data about Byzantine piracy can be found in The Venetian Claim Commission of 1278. There are detailed reports about pirates attacks in the Aegean Sea in this document. The Venetian Claim Commission of 1278 contains the Greek and non-Greek names of pirates. Perhaps some pirates were of Italian descent. The main pirates centers were Rhodes, Monemvasia, Anaea.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.989

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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 designObservational
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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueElectronic Archive of Ural Federal University (ELAR UrFU)Same topicMagnetic confinement fusion researchFrench-language works237,207