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Record W2168208141 · doi:10.1177/1740774507081218

Design of the fish oil inhibition of stenosis in hemodialysis grafts (FISH) study

2007· article· en· W2168208141 on OpenAlexafffund
Charmaine E. Lok, Michael Allon, Sandra Donnelly, Marc Dorval, Brenda R. Hemmelgarn, Louise Moist, Matthew J. Oliver, Marcello Tonelli, Kenneth Stanley

Bibliographic record

VenueClinical Trials · 2007
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of AlbertaHealth Sciences CentreSunnybrook Health Science CentreFoothills Medical CentreDr. Georges-L.-Dumont University Hospital CentreWestern UniversitySt. Michael's HospitalToronto General HospitalUniversity Health Network
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health Research
KeywordsMedicineRandomized controlled trialBlindingClinical endpointHemodialysisRandomizationClinical trialSurgeryStenosisAdverse effectPlaceboInternal medicinePathology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.059
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0590.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.370
GPT teacher head0.505
Teacher spread0.136 · 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 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

Citations24
Published2007
Admission routes2
Has abstractyes

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