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Record W3001171323 · doi:10.3389/fnmol.2019.00336

Terminological and Epistemological Issues in Current Memory Research

2020· article· en· W3001171323 on OpenAlexafffund
Oliver Hardt, Wayne S. Sossin

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
FundersCanadian Institutes of Health ResearchSimons Initiative for the Developing Brain
KeywordsTerminologyCognitive scienceAdaptive memoryPerceptionLimitingCognitive psychologyEngramFidelityCognitionComputer sciencePsychologyNeuroscienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

A number of observations in recent years demonstrates that across all levels of organization, memory is inherently fluid. On the cognitive-behavioral level, the innocent act of remembering can irrevocably alter the contents of established long-term memories, while the content of dormant long-term memories that is deemed irrelevant, superfluous, or limiting may be pragmatically erased or suppressed. On the cellular level, the proteins implementing the molecular alterations underpinning memories are in a constant state of flux, with proteins being turned over, translocated, reconfigured, substituted, and replaced. Yet, the general perception of memory, and the words used to describe it, suggest a static system characterized by the goal of preserving records of past experiences with high fidelity, in contrast to the reality of an inherently adaptive system purposed to enable survival in a changing world with a pragmatic disregard for the fate of acquired memories. Here, we examine present memory terminology and how it corresponds to our actual understanding of the molecules, cells, and systems underlying memory. We will identify where terms lead us astray and line out possible ways to reform memory nomenclature to better fit the true nature of memory as we begin to know it.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.251
GPT teacher head0.404
Teacher spread0.153 · 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.

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

Citations12
Published2020
Admission routes2
Has abstractyes

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