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Record W2994207888 · doi:10.28998/contegeo.v4i7.8363

FUNDAMENTOS TEÓRICOS DE MODELAGEM EM SISTEMAS COMPLEXOS

2019· article· pt· W2994207888 on OpenAlexaff
Mariana Tiné, Liliana Pérez, Roberto Molowny‐Horas

Bibliographic record

VenueRevista Contexto Geográfico · 2019
Typearticle
Languagept
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

<p>A geografia tem por definição o estudo do conjunto da Terra, que é por sua natureza extremamente complexo e depende de um número inesgótavel de elementos e relações entre os sistemas que o compõem. A complexidade do mundo atrai cada vez mais a comunidade científica com o inuito de melhor entender e representar as inúmeras interações que ocorrem na superfície, sobretudo no campo da geografia. A partir da teoria da complexidade várias foram as técnicas de modelagem computacional desenvolvidas a fim de simular o mundo real e antecipar possíveis eventos, como por exemplo a expansão urbana de uma determinada cidade, o desmatamento de uma área devido ao avanço da agricultura, e até mesmo padrões de imigração de uma população. É consenso que a modelagem será cada vez mais utilizada no planejamento territorial e ambiental, e este artigo traz uma breve explanação de alguns dos métodos mais comuns utlizados para estes fins.</p>

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)0.001
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.037

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 head0.033
GPT teacher head0.275
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

Explore more

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