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Record W7110643483

Pomorska baština kao turistički potencijal – Kvarner Maritime Heritage

2025· article· hr· W7110643483 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Zagreb University Computing Centre (SRCE) · 2025
Typearticle
Languagehr
FieldEconomics, Econometrics and Finance
TopicBalkan and Eastern European Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNational heritageTourismQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Kvarner ima dugu i snažnu povezanost s morem, što je oblikovalo njegov identitet, kulturu i gospodarstvo. Radi očuvanja i promocije maritimne baštine, Turistička zajednica Kvarnera 2019. godine razvila je brend Kvarner Maritime Heritage. Brendiranje je omogućilo sustavnu promociju maritimne baštine kroz kulturno-turističke proizvode i jačanje pozicije Kvarnera kao destinacije kulturnog turizma. Veliki doprinos razvoju brenda dale su aktivnosti provedene u sklopu EU projekata Mala barka, Mala barka 2 i Arca Adriatica. Ovdje treba posebno naglasiti uspješnu suradnju Turističke zajednice Kvarnera s Primorsko-goranskom županijom, koja je bila vodeći partner u navedenim projektima te s Pomorskim i povijesnim muzejom Hrvatskog primorja Rijeka. Velik doprinos u sustavnom pristupu očuvanja i revitalizacije pomorske baštine na Kvarneru dala je i Koordinacija udruga za očuvanje pomorske, ribarske i brodograđevne baštine Kvarnera i Istre - Tradicijska jedra Kvarnera i Istre. Brend uključuje mrežu od 90 interpretacijskih oznaka, 24 tematska itinerara, 16 obnovljenih tradicijskih barki, 5 velikih maritimnih manifestacija i 4 interpretacijska centra. Ove aktivnosti promoviraju pomorsku baštinu kroz edukacije, radionice, zabavne i interaktivne sadržaje, prilagođene širokoj publici, ali i mlađim uzrastima. Brend je prepoznat i na međunarodnoj razini, a danas predstavlja uspješan model povezivanja tradicije, turizma i lokalne zajednice u stvaranju autentičnog i održivog kulturnog proizvoda.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.152
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 teacher head, not a consensus.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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