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Record W4285469697 · doi:10.1186/s13012-021-01110-6

Proceedings from the 13th Annual Conference on the Science of Dissemination and Implementation

2021· article· en· W4285469697 on OpenAlexaff
Neta Gila, David Chambers, Lisa Simpson, Caroline Figueroa, Adrián Aguilera, Bibhas Chakraborty, Arghavan Modiri, Jai Aggarwal, Nina Deliu, Urmimala Sarkar, Joseph Jay Williams, Courtney R. Lyles, Eric D. A. Hermes, Robert A. Rosenheck, Laura Burrone, Carrie Lukens, Greg Dante, Steve Martino, Elizabeth J. Austin, Savitha Sangameswaran, Ms Segal, Lauren Drake, Denise Chang, Danielle C. Lavallee, Jonathan R. Olson, Alya Azman, Philip Benjamin, Kimberly M. Estep, Kimberly A. Coviello, Shannon Robshaw, Eric J. Bruns, David J. Kolko, Ian M. Bennett, Kimberly Hoagwood, Satish Iyengar, Heather M. Joseph, Kelly J. Kelleher, Amy M. Kilbourne, Elizabeth A. McGuier, Byron J. Powell, Maria Silva, Shawna N. Smith, Renee M. Turchi, Celeste Liebrecht

Bibliographic record

VenueImplementation Science · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Toronto
FundersUniversity of Washington
KeywordsMedical educationScholarshipAgency (philosophy)MedicinePanel discussionHealth services researchPublic relationsHealth carePolitical sciencePublic healthNursingSociologySocial science

Abstract

fetched live from OpenAlex

In the midst of a global pandemic and heightened national attention to the pervasiveness and impact of systemic racism, the 13 th Annual Conference on the Science of Dissemination and Implementation in Health focused on the theme of "Dissemination and Implementation Science in a Dynamic, Diverse, and Interconnected World: Meeting the Urgent Challenges of our Time." Cohosted by the National Institutes of Health and AcademyHealth in collaboration with our co-sponsors the Agency for Healthcare Research and Quality (AHRQ), the Patient Centered Outcomes Research Institute (PCORI), the Robert Wood Johnson Foundation (RWJF), and the US Department of Veterans Affairs (VA), the conference was held virtually December 15-17, 2020. While many virtual events attract fewer attendees than their in-person counterparts, the 2020 conference had the highest number of registrants: 1,587. As in prior years, a majority of attendees work in academic settings while 100 were students, 28 were patient scholarship recipients, and 133 participants joined us from 29 low-and middle-income countries. Over the three-day agenda, we hosted keynote and plenary sessions, concurrent podium and poster sessions, workshops and discussion forums, and multiple networking events. The call for abstracts generated 767 submissions, including individual paper presentations, individual posters, and panel presentations spread across nine thematic tracks. Over two hundred reviewers from multiple disciplines, sectors, settings, and career stages comprehensively assessed the abstracts within each track, coordinated by the track leads. New this year, we piloted a streamlined process for developing concurrent sessions for multiple tracks: We increased the number of reviewers per abstract for more robust scores, which were then used by track leads to assemble thematically relevant concurrent sessions among the most rigorous submissions. Both track leads and reviewers were extremely positive about the new process which we will fully implement going forward. This supplement includes 112 abstracts from the concurrent paper and panel sessions which represents a variety of dissemination and implementation research funded by our conference sponsors as well as other agencies, organizations, and systems. As in previous years, the conference was organized into nine thematic tracks: Behavioral Health, Clinical Care Settings (separated into two tracks: Patient-Level Interventions and System-Level Interventions), Global Dissemination and Implementation Science, Promoting Health Equity and Eliminating Disparities, Health Policy Dissemination and Implementation Science, Prevention and Public Health, and Models, Measures and Methods, and Building the Future of D & I Science: Training, Infrastructure, and Emerging Research Areas. This supplement is organized by these track themes. Slides and recordings of plenary and concurrent sessions (with the agreement of the authors)

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)0.008
metaresearch head score (Gemma)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0040.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
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 head0.541
GPT teacher head0.709
Teacher spread0.168 · 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 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
Published2021
Admission routes1
Has abstractyes

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