MétaCan
Menu
Back to cohort
Record W7145325781

ケロウナ産ハスカップの食品素材化に関する研究

2023· article· ja· W7145325781 on OpenAlexaboutno aff
孝之 藤原

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2023
Typearticle
Languageja
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPound (networking)Raw materialFood productsRecipeBaby food
DOInot available

Abstract

fetched live from OpenAlex

Haskap (Lonicera caerulea L.) cultivated in Kelowna, sister-city of Kasugai, is expected to be used for processed food in Japan. Currently, main form of available Haskap from Kelowna is frozen fruit. However, importing frozen Haskap from Canada to Japan is costly. In addition, frozen fruits are not suitable as food ingredients, due to the high moisture content and the need to thaw. Therefore, it is desirable to process Haskap into food raw materials in Canada, and export them to Japan. We prepared dried fruits and jams using frozen Haskap, and baked pound cakes using them. The dried Haskap and jam in the pound cake had a bright purple-red color, and the acidity of the dried fruit was refreshing. We will continue to study how to produce high-quality food ingredients using Haskap.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.057
GPT teacher head0.281
Teacher spread0.225 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInstitutional Repositories DataBase (IRDB)Same topicFood Quality and Safety StudiesFrench-language works237,207