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Record W2603417310

Taste Canada美味“加肴”

2016· article· ja· W2603417310 on OpenAlexaboutno aff
王小雷

Bibliographic record

Venue中国葡萄酒 · 2016
Typearticle
Languageja
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsTasteFood scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

主厨Ethan 本场加拿大美食盛宴出自大使馆主厨Ethan之手,这位年轻却成熟稳重的大厨来自加拿大阿尔伯塔省。由于父亲是在餐饮行业工作多年的美食家,Ethan自少受到熏陶,对美食美酒产生了浓厚的兴趣。2004年,他从餐厅洗碗工做起,正式踏入餐饮行业。期间他凭借自己的踏实努力与天赋,逐渐脱颖而出,成为一名主厨。之后,强烈的好奇心以及不断提升厨艺的动力促使他来到南阿尔伯塔理工学院进修专业烹饪课程,继续孜孜不倦地雕琢自己的厨艺。2013年,他通过层层选拔,来到了北京,担任驻华加拿大大使馆主厨。

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.025
Scholarly communication0.0120.008
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0170.001

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 head0.007
GPT teacher head0.182
Teacher spread0.175 · 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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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