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Record W2624289335 · doi:10.1055/s-2005-917500

INTRAOPERATIVE GEWEBECHARAKTERISIERUNG DURCH SPEKTRALANALYSE DER ULTRASCHALL-HOCHFREQUENZRÜCKSTREUDATEN VON HIRNGEWEBE UND MENINGEOMEN

2005· article· de· W2624289335 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUltraschall in der Medizin - European Journal of Ultrasound · 2005
Typearticle
Languagede
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Problemstellung: Zur Generierung von Ultraschall B-Bildern werden die Hochfrequenzsignale gleichgerichtet und nur die Einhüllende genutzt. Dabei gehen Informationen zum Frequenzgehalt des Ursprungssignals verloren. Aus diesem lassen sich aber spektrale Parameter errechnen, die zur Gewebecharakterisierung genutzt werden können. Die vorliegende Arbeit analysiert intraoperativ gewonnene Daten von Hirngewebe und Meningeomen und versucht eine auf Spektralparametern basierende Gewebecharakterisierung. Dies ist für die intraoperative Ultraschallbildgebung in der Neurochirurgie bedeutsam, da die Betrachtung herkömmlicher B-Bilder nicht immer eindeutig zwischen tumorösem und nicht-tumorösem Gewebe unterscheiden kann.

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.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.312
Teacher spread0.288 · 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