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Record W288768125 · doi:10.3136/nskkk.61.1

Development of an Egg Detection Sandwich ELISA Kit Using Monoclonal Antibodies

2014· article· en· W288768125 on OpenAlexaff
Shigekí Kato, Takahiro Yagi, Masanobu Akimoto, Keizo Arihara

Bibliographic record

VenueNippon Shokuhin Kagaku Kogaku Kaishi · 2014
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsConestoga Meat Packers (Canada)
Fundersnot available
KeywordsMonoclonal antibodyAntibodyMolecular biologyChemistryVirologyBiologyImmunology

Abstract

fetched live from OpenAlex

還元カルボキシメチル化した卵のオボアルブミンを免疫抗原として作製したモノクローナル抗体を用いて,特定原材料の通知法の抽出方法に対応した,新たな卵 ELISA キットを構築した.(1)作製したモノクローナル抗体は,2-ME と SDS で可溶化されたオボアルブミンを検出可能であった.さらに,複数のモノクローナル抗体を組み合わせることで,鶏,あひるおよびうずら卵白が検出可能であった.(2)構築した卵 ELISA キットの検出限界と定量限界はいずれも食品試料中の卵タンパク質濃度換算で1.0 μg/mL未満であり,表示が必要な数 μg/g レベルの測定には十分な感度であった.(3)添加回収試験では50 %以上,150 %以下の基準を満たし,再現性試験での CV%は全て10 %以下であった.さらに,卵以外の食品原材料では交差反応が認められなかった.(4)市販食品における食品表示と構築した卵 ELISA キットでの測定結果はすべて一致し,現行法と同等の測定値を示した.以上のことから,モノクローナル抗体のみで構築した卵 ELISA キットは,特定原材料の卵の定量検査法として通知法に示された現行法と同等に有用であることが考えられた.

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)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.048
GPT teacher head0.335
Teacher spread0.287 · 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
GenreMethods

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
Published2014
Admission routes1
Has abstractyes

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