MétaCan
Menu
Back to cohort
Record W4232427502 · doi:10.1109/nssmic.2003.1352223

RatCAP: miniaturized head-mounted PET for conscious rodent brain imaging

2003· article· en· W4232427502 on OpenAlexaff
P. Vaska, C. Woody, David J. Schlyer, Sepideh Shokouhi, S. P. Stoll, J.‐F. Pratte, P. O'Connor, S. Junnarkar, S. Rescia, B. Yu, M. L. Purschke, A. Kandasamy, Arantxa Villanueva, A. Kriplani, V. Radeka, N. Volkow, R. Lecomte, R. Fontaine

Bibliographic record

Venue2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515) · 2003
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPet imagingPositron emission tomographyComputer scienceAvalanche photodiodeParallaxMonte Carlo methodScannerBiomedical engineeringComputer visionNuclear medicineArtificial intelligenceMedicineDetectorMathematics

Abstract

fetched live from OpenAlex

Anesthesia is currently required for PET studies of the animal brain in order to eliminate motion artifacts. However, anesthesia profoundly affects the neurological state of the animal, complicating the interpretation of PET results. Furthermore, it precludes the use of PET to study the brain during natural behavior. The RatCAP tomograph (rat conscious animal PET) is designed to eliminate the need for anesthesia in rat brain studies. It is a miniaturized full-ring PET scanner which is attached directly to the head, covering nearly the entire brain. RatCAP utilizes arrays of 2 mm /spl times/ 2 mm LSO crystals coupled to matching avalanche photodiode arrays, which are in turn read out by full custom integrated circuits. Principal challenges have been addressed considering the physical constraints on size, weight, and heat generation in addition to the usual requirements of small-animal PET such as high spatial resolution in the presence of parallax error. A partial prototype has been constructed and preliminary measurements and optimization completed. Realistic Monte Carlo simulations have also been carried out to optimize system performance, which is predicted to be competitive with existing microPET systems.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.332
Teacher spread0.309 · 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 designBench or experimental
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

Citations8
Published2003
Admission routes1
Has abstractyes

Explore more

Same venue2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515)Same topicMedical Imaging Techniques and ApplicationsFrench-language works237,207