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Record W2214603472 · doi:10.4212/cjhp.v68i5.1492

Pharmacy Practice in Australia

2015· article· en· W2214603472 on OpenAlexvenueno aff
Rebekah Moles, Paulina Stehlik

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
FundersAmerican Association of Colleges of Pharmacy
KeywordsLife expectancyPopulationGeographyDemographyMainland ChinaIndigenousBirth rateInfant mortalityChinaMedicineFertilitySociology

Abstract

fetched live from OpenAlex

INTRODUCTION The Commonwealth of Australia is one of the wealthiest countries in the Western Pacific region, with a population estimated at over 23 million in 2013.1 About 27% of the population were born overseas, predominantly in the United Kingdom, New Zealand, China, and India,2 and 3% of the population are Indigenous Australians.3 Despite the country’s geographic size, Australia’s population is substantially lower than that of other regions of similar size4 because of a large, unin habitable central desert. Australia is divided into 6 states and 2 major mainland territories (Figure 1); in most respects, the 2 territories function as states. According to the Australian Bureau of Statistics, life expectancy is among the highest in the world and 25 years longer than a century ago. A baby boy born between 2010 and 2012 can expect to live to 79.9 years of age and a baby girl to 84.3 years;3 however, life expectancy for the Indigenous population is 10.6 years less for boys and 9.5 years less for girls. Like most developed nations, Australia has experienced a drop in birth rate and infant mortality. More specifically, infant mortality rates have fallen from 65.7 to 3.3 deaths per 1000 live births over the past 85 years.5,6 Decreased birth rates coupled with increased life expectancy mean that Australia exemplifies global trends, with an expanding older population. This article is the first in the series “International Perspectives on Pharmacy Practice”. For general information about the series, see the article elsewhere in this issue: Raman-Wilms L, Moles RJ. Widening our horizons: pharmacy practice from a global perspective. Can J Hosp Pharm. 2015;68(5):417. WHO Region:The Western Pacific Country: Australia

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.170
GPT teacher head0.507
Teacher spread0.337 · 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

Citations77
Published2015
Admission routes1
Has abstractyes

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