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Record W6958975057 · doi:10.6084/m9.figshare.18094495

Additional file 6 of Efficient non-contrast enhanced 3D Cartesian cardiovascular magnetic resonance angiography of the thoracic aorta in 3 min

2022· other· en· W6958975057 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsDescending aortaAortaThoracic aortaAortic archMean differenceSignificant difference

Abstract

fetched live from OpenAlex

Additional file 6: Figure S5. Bland–Altman plots for co-axial diameter measurements of mid aortic arch, mid descending aorta and distal descending aorta between the dNAV and the iNAV T2prep-bSSFP sequence for reviewer 2 (A, B, C) and reviewer 3 (D, E, F). Bland–Altman plots for co-axial diameter measurements of the mid aortic arch, mid descending aorta and distal descending aorta between the dNAV and the iNAV T2prep-bSSFP sequence for reviewer 2 (A, B, C) and reviewer 3 (D, E, F). The black line indicates the mean bias of the diameter measurements whereas the red lines represent the 95% confidence interval. Values are given in cm. A Good agreement with a mean difference 0.003 cm for reviewer 2 for the mid aortic arch (95% CI − 0.21 to 0.2) for reviewer 2; B good agreement with a mean difference of − 0.02 cm for reviewer 2 for the mid descending aorta (95% CI − 0.2 to 0.15); C good agreement with a mean difference of 0.03 cm for reviewer 2 for the distal descending aorta (95% CI − 0.13 to 0.2); D good agreement with a mean difference of 0.01 cm for reviewer 3 for the mid aortic arch arch (95% CI − 0.31 to 0.33); E good agreement with a mean difference of 0.006 cm for reviewer 3 for the mid descending aorta (95% CI − 0.25 to 0.29); F good agreement with a mean difference of − 0.02 cm for reviewer 3 for the distal descending aorta (95% CI − 0.25 to 0.2).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.978
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.9780.000

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 head0.008
GPT teacher head0.179
Teacher spread0.171 · 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
GenreDataset

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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