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Record W7002187468

Nestle India welcomes court order to tests Maggi Noodles

2015· other· en· W7002187468 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternet Archive (Internet Archive) · 2015
Typeother
Languageen
FieldEnvironmental Science
TopicAerospace, Electronics, Mathematical Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsNoticeOrder (exchange)Agency (philosophy)AccreditationUnit (ring theory)Product (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Nestlé wants its banned noodles back on the shelves of shops in India. The popular 2-Minute noodle snack Maggi, was removed from stores a few months ago after unsafe levels of lead were found. There was also concern it contained the chemical flavor enhancer M-S-G, which isn't mentioned in the list of ingredients. Nestlé challenged the call and took regulators to court, saying the samples weren't tested at accredited labs and the company never got a show-cause notice before the ban was issued. The Mumbai High Court ruled that Nestle India can start manufacturing and selling noodles 6 weeks from now if tests at 3 different Indian laboratories declare it safe. Nestle's Indian arm also exports Maggi noodles to the U-S, the U-K, Canada, Singapore, and other countries. The U-K Food Standards Agency says Maggi-branded noodles made by the Indian unit of Nestle are safe to eat, and the lead content is well within E-U permitted levels.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0340.038

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 head0.014
GPT teacher head0.248
Teacher spread0.234 · 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