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Record W1909136707 · doi:10.1002/cmmi.1555

A comprehensive review on controls in molecular imaging: lessons from MMP‐2 imaging

2014· review· en· W1909136707 on OpenAlexafffund
Réjean Lebel, Martin Lepage

Bibliographic record

VenueContrast Media & Molecular Imaging · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsMatrix metalloproteinaseMolecular imagingModality (human–computer interaction)ModalitiesMedicineComputer scienceBioinformaticsArtificial intelligenceBiologyInternal medicineBiotechnology

Abstract

fetched live from OpenAlex

Metalloproteinases (MMPs), including MMP-2, play critical roles in tissue remodeling and are involved in a large array of pathologies, including cancer, arthritis and atherosclerosis. Their prognostic value warranted a large investment or resources in the development of noninvasive detection methods, based on probes for many current clinical and pre-clinical imaging modalities. However, the potential of imaging techniques is only matched by the complexity of the data they generate. This complexity must be properly assessed and accounted for in the early steps of probe design and testing in order to accurately determine the efficacy and efficiency of an imaging strategy. This review proposes basic rules for the evaluation of novel probes by addressing the specific case of MMP targeted probes.

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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.017
GPT teacher head0.310
Teacher spread0.293 · 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
GenreReview

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

Citations26
Published2014
Admission routes2
Has abstractyes

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