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Record W2966097614 · doi:10.1186/s13012-019-0922-2

Implementation Science and Implementation Science Communications: our aims, scope, and reporting expectations

2019· editorial· en· W2966097614 on OpenAlex

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

VenueImplementation Science · 2019
Typeeditorial
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsScope (computer science)Transparency (behavior)Public relationsHealth informaticsHealth services researchOpen scienceHealth administrationQuality (philosophy)Health careScience communicationMedicinePublic healthPolitical scienceComputer scienceScience educationNursing

Abstract

fetched live from OpenAlex

In the 13 years since the inception of Implementation Science, we have witnessed a continued rise in the number of submissions, reflecting the growing global interest in methods to enhance the uptake of research findings into healthcare practice and policy. We now receive over 800 submissions annually, and there is a large gap between what is submitted and what gets published. To better serve the needs of the research community, we announce our plans to introduce a new journal, Implementation Science Communications, which we believe will support publication of types of research reports currently not often published in Implementation Science. In this editorial, we state both journals' scope and current boundaries and set out our expectations for the scientific reporting, quality, and transparency of the manuscripts we receive.

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)0.052
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0520.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.011
Science and technology studies0.0170.006
Scholarly communication0.0020.009
Open science0.0040.004
Research integrity0.0000.002
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 head0.655
GPT teacher head0.765
Teacher spread0.110 · 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