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Record W2610743595 · doi:10.1097/nnd.0000000000000357

Creating a Novel Online Digital Badge-Awarding Program in Patient Navigation to Address Healthcare Access

2017· article· en· W2610743595 on OpenAlex
Annie Rohan, Judith T. Fullerton, Lori A. Escallier, Susmita Pati

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

VenueJournal for Nurses in Professional Development · 2017
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsCentre for Advancing Health Outcomes
FundersAmerican College of SurgeonsRobert Wood Johnson Foundation
KeywordsBlackboard (design pattern)CurriculumMedical educationComputer scienceHealth careQuality (philosophy)MultimediaHealth professionalsWorld Wide WebPsychologyMedicinePedagogySoftware engineering

Abstract

fetched live from OpenAlex

A novel, sustainable digital badge-awarding online course was developed to prepare learners with familiarity of patient navigation. Learners offered favorable endorsement of essentially all elements of the program, especially the utility of the Blackboard learning management software program. Quality Matters standards provided a rigorous framework for the challenges of designing, implementing, and evaluating online curricula. Online education is an effective method for meeting the professional development needs of those seeking careers in care coordination/patient navigation.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.487
Teacher spread0.421 · 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