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Record W1516645885 · doi:10.24302/drd.v2i1.197

Evolução e estágio do desenvolvimento regional: o caso das regiões do Paraná

2012· article· pt· W1516645885 on OpenAlexfundno aff
Paulo Henrique de Cezaro Eberhardt, Jandir Ferrera de Lima

Bibliographic record

VenueDRd - Desenvolvimento Regional em debate · 2012
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsnot available
FundersUniversidade Estadual do Oeste do ParanáFundação AraucáriaConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversité du Québec à Chicoutimi
KeywordsCuritibaHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

O objetivo deste artigo foi analisar o perfil e o estágio de desenvolvimento regional das regiões do Estado do Paraná. Para isso, foi elaborado um Índice de Desenvolvimento Regional utilizando-se variáveis econômicas e sociais. Os resultados mostraram que a microrregião de Curitiba se desenvolveu em um ritmo mais acelerado que as demais regiões paranaenses, com exceção da microrregião de Paranaguá, que obteve uma variação do nível de desenvolvimento maior que a de Curitiba. As regiões classificadas como avançadas no estágio de desenvolvimento regional não se alteraram entre 2000 e 2007. As regiões classificadas como em transição diminuiu aumentando o número de regiões classificadas como retardatárias, em função do ritmo mais acelerado de desenvolvimento da microrregião de Curitiba.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.287
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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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