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Record W4312553584 · doi:10.1055/s-0042-1755847

Romosozumab verbessert vertebrale kortikale Knochenmasse und -struktur im Vergleich zu Teriparatid signifikant: HR-QCT-Analyse aus randomisierter Studie bei postmenopausalen Frauen mit niedriger BMD

2022· article· de· W4312553584 on OpenAlexaff
Timo Damm, Cesar Libanati, Jaime Peña, G. Campbell, Reinhard Barkmann, Angeles Hanley, Stefan Goemaere, A Michael Bolognese, Christopher Recknor, C. Mautalén, YC Yang, Claus‐C. Glüer

Bibliographic record

VenueOsteologie/Osteology · 2022
Typearticle
Languagede
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineGynecologyMaterials science

Abstract

fetched live from OpenAlex

Einleitung Das Verständnis der Wirkung von Osteoporosetherapien an der Wirbelsäule ist für die Knochenbiologie und die klinische Praxis von großer Bedeutung. Wir haben ein verbessertes Verfahren entwickelt, das auf einer komplexe 3D-Segmentierung des Wirbelkörperkortex auf hochauflösenden quantitativen Computertomografiescans (HR-QCT) von T12-Wirbelkörpern basiert, um spezifische Veränderungen der Knochenmineraldichte (BMD) und der Mikrostruktur zu bestimmen.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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