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Record W2265434961 · doi:10.1177/2168479015597730

Applying Regulatory Science to Develop Safe and Effective Medicines for Neonates: Report of the US Food and Drug Administration First Annual Neonatal Scientific Workshop, October 28–29, 2014

2015· article· en· W2265434961 on OpenAlexaff
Martin Offringa, Jonathan M. Davis, M. Turner, Robert M. Ward, Ralph Bax, Sam Maldonado, Vikram Sinha, Susan McCune, Anne Zajicek, Daniel K. Benjamin, Christina Bucci‐Rechtweg, Robert M. Nelson

Bibliographic record

VenueTherapeutic Innovation & Regulatory Science · 2015
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsSickKids FoundationInstitute for Clinical Evaluative SciencesHospital for Sick Children
FundersJanssen PharmaceuticalsU.S. Department of Health and Human Services
KeywordsFood and drug administrationMedicineRegulatory scienceIntensive care medicinePharmacyScientific evidenceRetinopathy of prematurityNeonatal sepsisDrugClinical trialPharmacologyFamily medicineSepsisSurgeryPregnancyBiologyPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.352
Teacher spread0.305 · 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

Citations9
Published2015
Admission routes1
Has abstractno

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