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Record W2947519283 · doi:10.46311/2318-0579.55.euj2466

FLUORETAÇÃO NO ABASTECIMENTO PÚBLICO: ESTUDO DE CASO EM UBERABA-MG

2018· article· pt· W2947519283 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Uningá · 2018
Typearticle
Languagept
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesChemistryPhilosophy

Abstract

fetched live from OpenAlex

O objetivo deste trabalho foi verificar as concentrações de flúor nas águas de abastecimento público na cidade de Uberaba, com finalidade de observar se a quantidade de flúor empregada é suficiente para prevenir a cárie dentária e se está de acordo com a legislação vingente. Para medir a quantidade de flúor na água foi utilizado método espectrofotométrico e kit da Merck®. Constatou-se que todas as regiões amostradas apresentaram concentrações de flúor satisfatórias conforme Portaria do Ministério da Saúde. Em função das controvérsias quanto à fluoretação da água de abastecimento público, novos estudos são necessários para determinar o melhor método para prevenção da cárie dentária.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.010

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 head0.028
GPT teacher head0.309
Teacher spread0.281 · 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