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Record W3014415052 · doi:10.1080/0964704x.2020.1738838

White matter—Maximien Parchappe and the integration of articulate language

2020· article· en· W3014415052 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

VenueJournal of the History of the Neurosciences · 2020
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsWhite matterPsychologyWhite (mutation)LinguisticsCognitive sciencePhilosophyMedicineChemistryMagnetic resonance imaging

Abstract

fetched live from OpenAlex

The Imperial Academy of Medicine of Paris met in the spring of 1865 to discuss the localization of speech. One of the participants was Maximien Parchappe (1800-1866), an alienist whose research interests lay in the cerebral cortex. This article addresses Maximien Parchappe's concept that the cognitive elements of language-such as the translation of thoughts into words, the will to express them, and the means to do so-reside within the cortical gray matter, and that they are integrated through white-matter fibers. In so doing, Parchappe anticipated Carl Wernicke's linking of the posterior aspects of the dominant frontal and temporal lobes in verbal expression, and Jules Dejerine's linking of the angular gyrus and Wernicke's area in the understanding of written language. Functional imaging has revived interest in language as a network of neuronal aggregates and has given new relevance to Parchappe's concept of the functional organization of language.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.332

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.262
Teacher spread0.234 · 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