MétaCan
Menu
Back to cohort
Record W1984276393 · doi:10.1017/s1355617700633167

In Memoriam

2000· article· en· W1984276393 on OpenAlexaboutno aff
Kenneth M. Adams

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipExcellenceNeuropsychologyPsychologyQuarter (Canadian coin)Embodied cognitionPsychoanalysisSociologyCognitive scienceEpistemologyPolitical sciencePhilosophyCognitionLawHistoryNeuroscience

Abstract

fetched live from OpenAlex

Laird Cermak was to become President of INS in February 2000, taking over the responsibilities for leading a scientific society he loved and served for over a quarter of a century. In many ways he embodied the very values the INS has always hoped to promote in excellence of scholarship, keen interest in behavioral neurosciences, and an easy and reflexive interdisciplinary citizenship. His name has been synonymous with a distinctive line of intellectual inquiry in amnesia and memory mechanisms for as long as I have been in neuropsychology myself.

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)0.003
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0040.014
Insufficient payload (model declined to judge)0.0480.043

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 head0.040
GPT teacher head0.323
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the International Neuropsychological SocietySame topicNeuroscience, Education and Cognitive FunctionFrench-language works237,207