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Record W2335427734 · doi:10.3136/nskkk.59.378

Media for Detecting Lactic Acid Spoilage Bacteria Isolated from Cured Cooked Meat Products

2012· article· en· W2335427734 on OpenAlexaff
Naoko Kamisaki-Horikoshi, Yukio Okada, Kazuko Takeshita, Takashi Sameshima, Keizo Arihara

Bibliographic record

VenueNippon Shokuhin Kagaku Kogaku Kaishi · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsConestoga Meat Packers (Canada)
Fundersnot available
KeywordsFood spoilageFood scienceLactic acidCooked meatMeat spoilageBacteriaChemistryBiology

Abstract

fetched live from OpenAlex

食肉製品製造工場における汚染乳酸菌を対象に,簡便で高感度に検出する改良培地と培養条件を検討するとともに,RAPD-PCR 法などを利用した食肉製品製造工場における汚染源解析を試みた.(1) BCP 添加 APT broth からグルコース濃度,寒天濃度,緩衝能を調整した LA 培地は,既存の培地に比べ高感度に乳酸菌を検出できた.(2) LA 培地は,25°C で 48 時間培養することにより,食肉製品製造工場から分離した汚染乳酸菌を含む供試乳酸菌230株中の97%を検出し,さらに 24 時間培養することで全体の 99.6% を検出した.(3) LA 培地は試験管内の培地全体において指示薬の色の変化が鮮明になるため,LA 培地を用いることによって,効果的に汚染乳酸菌を検出できることが明らかとなった.(4) LA 培地を用いて食肉製品製造工場の汚染乳酸菌を検査,分離し,RAPD-PCR 法と 16SrDNA 解析を利用することにより,製品を汚染している乳酸菌の汚染源を特定できることが確認され,衛生改善に役立つことが実証された.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

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

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 head0.036
GPT teacher head0.233
Teacher spread0.197 · 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 teacher head, 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
Published2012
Admission routes1
Has abstractyes

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