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Evaluating Cultural Routes for a Network of Competitive Cities in the Mediterranean Sea: The Eastern Monasticism in Western Mediterranean Area

2014· article· en· W2014367201 on OpenAlexaboutno aff
Francesco Calabrò, Daniele Campolo, Giuseppina Cassalia, Carmela Tramontana

Bibliographic record

VenueAdvanced materials research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsMediterranean climateGeographyCharterDestiny (ISS module)Mediterranean seaNatural (archaeology)Mediterranean areaHistoryEthnologyArchaeology

Abstract

fetched live from OpenAlex

Calabria region (Southern Italy) has become the nerve center of historical events, decisive for the Mediterranean sea destiny, because of its geographical position, its centrality in the Mediterranean area, the peculiarities of the district and the wealth of natural resources. The effects of its role in the Mediterranean history are still visible in its natural, urban and social structure, thus giving the region a large number of cultural and environmental values, which find root in the three preceding millennia. The paper, starting from the most historic routes that have affected the Calabrian coast, aims to highlight the one that has the greatest impact on the culture of the region trying to figure out if it is possible to identify, protect and promote a cultural route according to the ICOMOS Charter of Cultural Routes criteria, devised by the ICOMOS’ international Scientific Committee of Cultural Routes (CIIC) and ratified by the 16th General Assembly of ICOMOS, in Quebec (Canada), October 4, 2008.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.200
GPT teacher head0.420
Teacher spread0.219 · 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
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

Citations7
Published2014
Admission routes1
Has abstractyes

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