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Record W2808970193 · doi:10.1016/j.pmedr.2018.06.008

Assessing hearing and cognition challenges in consumer processing of televised risk information: Validation of self-reported measures using performance indicators

2018· article· en· W2808970193 on OpenAlexfundno aff
Brian G. Southwell, Sarah Parvanta, Mihaela Johnson, Amie C. O’Donoghue, Helen W. Sullivan, Sarah Ray, Christine Davis, Nancy M. McKenna

Bibliographic record

VenuePreventive Medicine Reports · 2018
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
FundersUniversity of North Carolina at Chapel HillHamilton Health Sciences FoundationUniversity of MinnesotaU.S. Department of Health and Human Services
KeywordsAudiologistCognitionRecallHearing lossPsychologyAudiologyClinical psychologyTask (project management)Effects of sleep deprivation on cognitive performanceMedicineCognitive psychologyPsychiatry

Abstract

fetched live from OpenAlex

= 1064) in North Carolina, USA, in 2017. We found moderate correspondence between self-reported hearing loss and audiologist-assessed hearing loss. Both measures also showed a small negative association with recall of presented risk information. Cognitive ability results suggested less substantial correspondence between self report and performance task and the measures differed in predicting risk recall. Our results suggested a moderately efficient measure for hearing ability for research on risk information exposure and retention, and yet also suggested the need for caution regarding future use of self-reported cognitive ability as a substitute for a performance-based measure.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.167
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.415
Teacher spread0.298 · 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.

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

Citations6
Published2018
Admission routes1
Has abstractyes

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