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Record W2117030014 · doi:10.3109/00207450109149757

Normal Spatial Memory Following Postseizure Treatment with Ketamine: Selective Damage Attenuates Memory Deficits in Brain-Damaged Rodents

2001· article· en· W2117030014 on OpenAlexaff
S. A. Santi, Lisa Cook, Michael A. Persinger, Rodney P. O’Connor

Bibliographic record

VenueInternational Journal of Neuroscience · 2001
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsLaurentian University
Fundersnot available
KeywordsKetamineStatus epilepticusAcepromazineThalamusNeuroscienceNeuroprotectionAnesthesiaVigilance (psychology)HippocampusMedicineEntorhinal cortexPsychologyInternal medicineEpilepsy

Abstract

fetched live from OpenAlex

Within 30 min after the initiation of status epilepticus (SE) by lithium and pilocarpine, rats were injected with either acepromazine or ketamine. Compared to the rats that had received the acepromazine, the group that had received the ketamine displayed more accurate spatial memory. Their scores did not differ significantly from normal (non-seized) controls. Although the ketamine treatment did not significantly change the amount of neuronal loss within about 100 Paxinos and Watson structures, it was neuroprotective for several structures within the thalamus and portions of the temporal and parietal cortices. Ketamine-treated rats, however, displayed markedly more damage within the entorhinal cortices and amygdalohippocampal area.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.341
Teacher spread0.306 · 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 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

Citations22
Published2001
Admission routes1
Has abstractyes

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