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Industry-Sponsored Clinical Research in Academia

2016· book-chapter· en· W2582066147 on OpenAlexfundno aff
Italo Biaggioni

Bibliographic record

VenueClinical and Translational Science · 2016
Typebook-chapter
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory HealthNational Center for Advancing Translational SciencesGeorgia Clinical and Translational Science Alliance
KeywordsEngineering ethicsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

The development of new therapies relies on industry-sponsored clinical research (ISCR) and academic health centers should play a role in this process. Here we discuss the challenges involved that arise from different priorities and perceptions. Financial and efficiency forces have resulted in a greater proportion of ISCR being done outside academic health centers, a trend that is likely to continue. We propose a framework that considers the perspectives from industry, academia, academic investigators and patients, and potential models of institutional support that can facilitate the involvement of academia in ISCR.

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)0.034
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.009
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0050.019
Insufficient payload (model declined to judge)0.0010.000

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 head0.716
GPT teacher head0.645
Teacher spread0.071 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreOther

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

Citations1
Published2016
Admission routes1
Has abstractyes

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