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In the Path of Conquest

2020· book· en· W4241465808 on OpenAlexaff
Waldemar Heckel

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCONQUESTPath (computing)HistoryComputer scienceAncient historyProgramming language

Abstract

fetched live from OpenAlex

Abstract This book offers a fresh insight into the conquests of Alexander the Great by attempting to view the events of 336–323 from the vantage point of the defeated. The extent, and form, of the resistance of those whose territories were invaded varied in accordance with previous relationships with either the Macedonian invader or the Achaemenids. The internal political situations of many states—particularly the Greek cities of Asia Minor—were also a factor. In the vast Persian Empire from the Aegean to the Indus, some states surrendered voluntarily, and others offered fierce resistance. Not all regions were subdued through military actions. Indeed, the excessive use of force on Alexander’s part is demonstrated as ineffective and counterproductive. This book examines the reasons for these varied responses, giving more emphasis to the defeated and less to the Conqueror and his Macedonians. In the process, it debunks many long-held views concerning Alexander’s motives. Such a study involves rigorous analysis of the ancient sources, and their testimony is presented throughout the book in the form of newly translated passages.

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)0.002
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.014
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.271
Teacher spread0.245 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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