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Record W2511643197 · doi:10.1002/lite.201600040

Moving science forward in a competitive marketplace

2016· article· en· W2511643197 on OpenAlexaffabout
Kelley Fitzpatrick

Bibliographic record

VenueLipid Technology · 2016
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsIMRIS (Canada)
Fundersnot available
KeywordsLinumCompetitive advantageProduct (mathematics)BusinessAgricultural scienceAgricultureAgricultural economicsMarketingBiotechnologyAgronomyBiologyEconomicsEcology

Abstract

fetched live from OpenAlex

Scientific information is the foundation of the food and health market, the availability of which can influence the success of a product and provide a competitive advantage. Flaxseed (Linum usitatissimum) has a significant advantage in this regard as it has strong clinical efficacy data that can be used to build consumer and food product company interest. Flax is an oilseed that is grown in cool, northern climates such as found in the western Canadian prairies and northern U.S. It can be consumed in whole seed, meal or oil form.

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)0.040
metaresearch head score (Gemma)0.042
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.105
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0070.012
Scholarly communication0.0390.051
Open science0.0030.021
Research integrity0.0240.020
Insufficient payload (model declined to judge)0.1050.043

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 head0.006
GPT teacher head0.252
Teacher spread0.246 · 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
GenreCommentary

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 routes2
Has abstractyes

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