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Record W4391516869 · doi:10.53555/sfs.v10i1s.2123

CAVIAR THE GOLD IN YOUR SPOONA

2023· article· en· W4391516869 on OpenAlexvenueno aff
Sagarika Mandal, Saheli Ghosal, Indrajit Karmakar, Krishnendu Biswas, Anapurba kanjilal

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Caviar is the unhatched roe of certain species of sturgeon and is used as an appetiser around the world. Caviar is famous for a number of reasons, most notably its exorbitant cost and its salty, nutty, and luscious flavour.Over the past 30 years, natural sturgeon populations have declined dramatically, and a rising demand for caviar has prompted the development of sturgeon farming for the production of caviar.Caviar passes through a lengthy procedure from fish to plate. Beluga, Sterlet, Kaluga hybrid, Ossetra, Siberian sturgeon, and Sevruga are the most popular forms of caviar produced by sturgeon species indigenous to the Caspian Sea.Premium caviar is extremely perishable.Typically sold in vacuum-sealed containers, premium caviar lasts 2-4 weeks unopened.caviar has always been a "meal of the privileged," and appropriately so. Pearl- sized pearls erupt in the mouth and taste fishy. Yet, caviar was previously a luxury. Historically, Russian fishermen ate caviar. Caviar on top of hot, cooked potatoes was a staple. Russian fishermen call caviar "roe".It has abundant usage in the culinary world. Including health benefits selenium is abundant in caviar and acts in tandem alongside vitamin E to prevent free radical damage to cells.Caviar's omega-3 fatty acids improve mood and cognition, making it a popular treatment for depression and bipolar illness.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.322
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3220.158

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 head0.367
GPT teacher head0.289
Teacher spread0.077 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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