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Record W2312015575 · doi:10.1109/tsmcc.2006.871151

Cognitive informatics models of the brain

2006· article· en· W2312015575 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · 2006
Typearticle
Languageen
FieldComputer Science
TopicCognitive Computing and Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCognitive scienceCognitionComputer scienceCognitive psychologyLIDACognitive neuropsychologyPsychologyCognitive modelNeuroscienceNeuropsychology

Abstract

fetched live from OpenAlex

The human brain is the most complicated organ in the universe and a new frontier yet to be explored by an interdisciplinary approach. This paper attempts to develop logical and cognitive models of the brain by using cognitive informatics and formal methodologies. This paper adopts a memory-based approach to explore the brain and to demonstrate that memory is the foundation for any kind of natural or artificial intelligence. Logical structures of memories are explored, and cognitive models of the brain are proposed. Cognitive mechanisms of the brain, including hypotheses and theories on the thinking engine of the brain, long-term memory establishment, and roles of perceptive eye movement, and sleep in long-term memory development, are investigated. The models and theories can be applied to explain a wide range of fundamental phenomena in psychology, cognitive science, physiology, computing, and neural science.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.245
Teacher spread0.222 · 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