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Record W4406862017 · doi:10.57598/r22a

HTA Positronen Emissie Tomografie in België

2005· book· nl· W4406862017 on OpenAlexfundno aff
Irina Cleemput, Guy Dargent, J Poelmans, C Camberlin, Dirk Ramaekers

Bibliographic record

Venuenot available
Typebook
Languagenl
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsnot available
FundersMinnesota Department of HealthAgency for Healthcare Research and QualityCenters for Medicare and Medicaid ServicesInternational Network of Agencies for Health Technology AssessmentCanadian Institutes of Health ResearchHealth Technology Assessment internationalAlberta Heritage Foundation for Medical ResearchInstitute for Clinical Evaluative SciencesFondation pour la Recherche MédicaleMultiple System Atrophy CoalitionInstitut National d'assurance Maladie-InvaliditéU.S. National Library of MedicineU.S. Department of Veterans Affairs
KeywordsPsychology

Abstract

fetched live from OpenAlex

Het Federaal Kenniscentrum voor de Gezondheidszorg (KCE) heeft zopas een rapport over Positron Emission Tomography (PET) gepubliceerd in de reeks 'Health Technology Assessments'. PET is een technologie voor medische beeldvorming die vooral wordt toegepast bij bepaalde vormen van kanker.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.006

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 head0.019
GPT teacher head0.313
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2005
Admission routes1
Has abstractyes

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