MétaCan
Menu
Back to cohort
Record W2024551447 · doi:10.1074/jbc.x600004200

Lectins: Carbohydrate-specific Reagents and Biological Recognition Molecules

2006· review· en· W2024551447 on OpenAlexaboutno aff
Nathan Sharon

Bibliographic record

VenueJournal of Biological Chemistry · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsnot available
Fundersnot available
KeywordsGlycobiologyChemistryBiochemistryGlycoprotein

Abstract

fetched live from OpenAlex

The occurrence in nature of proteins with hemagglutinating activity that in later years were shown to be sugar-specific and eventually named lectins has been known since the turn of the 19th century, but until about two decades ago they aroused little interest (for a historical survey, see Ref. 1). My own involvement with these proteins began inadvertently and initially on a part-time basis in the early 1960s after my return to the Weizmann Institute from two and a half years of exciting and educational postdoctoral studies in the United States.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.013

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 head0.100
GPT teacher head0.335
Teacher spread0.235 · 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
GenreReview

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

Citations448
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biological ChemistrySame topicGlycosylation and Glycoproteins ResearchFrench-language works237,207