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Record W2794601824 · doi:10.1097/bsd.0000000000000588

Explanatory Versus Pragmatic Trials

2017· article· en· W2794601824 on OpenAlexaff
Zamir Merali, Jefferson R. Wilson

Bibliographic record

VenueClinical Spine Surgery A Spine Publication · 2017
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsGeneralizability theoryClinical trialMedicineExternal validityGrading (engineering)Randomized controlled trialInternal validityResearch designMedical physicsPhysical therapyPsychologySurgeryPathologyStatistics

Abstract

fetched live from OpenAlex

Randomized clinical trials often represent the highest level of clinical evidence available to evaluate the efficacy of an intervention in clinical medicine. Although the process of randomization serves to maximize internal validity, the external validity, or generalizability, of such studies depends on several factors determined at the design phase of the trial including eligibility criteria, study setting, and outcomes of interest. In general, explanatory trials are optimized to demonstrate the efficacy of an intervention in a highly selected patient group; however, findings from these studies may not be generalizable to the larger clinical problem. In contrast, pragmatic trials attempt to understand the real-world benefit of an intervention by incorporating design elements that allow for greater generalizability and clinical applicability of study results. In this article we describe the explanatory-pragmatic continuum for clinical trials in greater detail. Further, a well-accepted tool for grading trials on this continuum is described, and applied, to 2 recently published trials pertaining to the surgical management of lumbar degenerative spondylolisthesis.

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)0.007
metaresearch head score (Gemma)0.101
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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 score0.834
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.101
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0020.001

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 head0.304
GPT teacher head0.490
Teacher spread0.186 · 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

Citations30
Published2017
Admission routes1
Has abstractyes

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