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Record W2133843295 · doi:10.1109/waina.2009.74

A SOA-Based Collaborative Environment for Clinical Trials on Neglected Diseases

2009· article· en· W2133843295 on OpenAlexaff
Maria Beatriz Felgar de Toledo, Olga Nabuco, Marcos Rodrigues, Diego Garcia, Miriam A. M. Capretz, Marcelo Fantinato, Itana Maria de Souza Gimenes, Rodrigo Bonacin, Ana Carolina Guerra, Tarcísio da Rocha, Laura Cristina Simões Viana

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsWestern University
Fundersnot available
KeywordsWorkflowReuseMetadataProtocol (science)Computer scienceClinical trialData sharingPopulationKnowledge managementProcess managementData scienceWorld Wide WebDatabaseMedicineBusinessEngineeringEnvironmental health

Abstract

fetched live from OpenAlex

The WebInVivo project aims at providing automated support for clinical research on neglected diseases. It includes mechanisms for (a) sharing and reusing clinical trial assets, such as protocols, protocol data, workflows and workflow metadata and (b) controlling the protocol life cycle, from modelling to execution. In this project, collaboration in the biomedical area will permeate three segments of Brazilian society: (a) research and development, (b) health agents and (c) population at risk. The knowledge gained from this study will be complied and published through social networks directed to these segments of Brazilian society.

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)0.012
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.531
GPT teacher head0.572
Teacher spread0.040 · 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 designNot applicable
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

Citations3
Published2009
Admission routes1
Has abstractyes

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