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Record W2421822448 · doi:10.1385/0-89603-275-2:329

Synthetic Antibody Gene Libraries for In Vitro Affinity Maturation

2003· article· en· W2421822448 on OpenAlexaff
Su-Jun Deng, C. Roger MacKenzie, Saran A. Narang

Bibliographic record

VenueHumana Press eBooks · 2003
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsAntibody RepertoireOligonucleotidePhage displayAntibodyImmunizationGeneGenomic libraryComputational biologyBiologyAntigenIn vitroMolecular biologySynthetic biologyGeneticsBase sequence

Abstract

fetched live from OpenAlex

The application of phage display to the screening of antibody V-gene libraries promises to replace animal immunization and hybridoma technology as a means of antibody generation (,). Synthetic libraries offer the potential for expanding the immune system repertoire and designing libraries for particular sets of antigens. We have developed a method for the generation of synthetic antibody gene libraries by which spiked oligonucleotides are assembled by a ligase chain reaction protocol (). This is a synthetic adaptation of a reaction that was previously used as a diagnostic tool (,).

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.082
GPT teacher head0.342
Teacher spread0.261 · 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 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

Citations2
Published2003
Admission routes1
Has abstractyes

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