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Record W3112211600 · doi:10.31372/20200503.1093

Aholoa Lāna‘i!

2020· article· en· W3112211600 on OpenAlexvenueno aff
May K. Kealoha

Bibliographic record

VenueAsian/Pacific Island Nursing Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsnot available
FundersUniversity of Hawai'i at Mānoa
KeywordsPacific islandersCensusAsthmaDemographyEthnic groupMetropolitan areaGeographyPopulationPublic healthDisease controlPopulation healthGerontologyMedicineEnvironmental healthPolitical scienceSociologyArchaeology

Abstract

fetched live from OpenAlex

Asthma is a major public health concern for the state of Hawai‘i, where 10% of adults reported current asthma status in 2016 (Centers for Disease Control and Prevention, 2018). Each county reported high prevalence rates: Hawai‘i, 19.6%; Honolulu, 17.3%; Kaua‘i, 15.4%; Maui, 17.2% (Hawai‘i Health Data Warehouse, 2016). Lāna‘i is the smallest island in the State consisting of 141 square miles and a population of 3,102 (U.S. Census Bureau, 2018). Although robust asthma data exist for metropolitan Honolulu, statistics are unavailable for Lāna‘i. If data were to be extrapolated using whole ethnic populations and adult asthma rates (Hawai‘i Health Data Warehouse, 2016), 184 (13%) Filipinos and 200 (28.4%) part-Hawaiian and other Pacific Islanders may be affected by the condition.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.379
Teacher spread0.325 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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