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Record W3116012584 · doi:10.31590/ejosat.747799

Siyah Kuşburnu Meyvesinden Süperkritik CO2 Ekstraksiyonu ile Doğal Pigment Eldesinin Yüzey Yanıt Yöntemi Kullanılarak Modellenmesi ve Optimizasyonu

2020· article· tr· W3116012584 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Science and Technology · 2020
Typearticle
Languagetr
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsSupercritical carbon dioxideExtraction (chemistry)SolventPigmentChemistryEthanolAnthocyaninChromatographyCarbon dioxideSupercritical fluid extractionBar (unit)Supercritical fluidResponse surface methodologyMaterials scienceFood scienceBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Bu almada siyah kuburnu meyvesi ierdii antosiyaninlerden dolay doal pigment kayna olarak kullanlmtr. Sz konusu pigmentleri elde etmek iin yeil teknoloji olarak deerlendirilen ve organik zgen kalnts brakma riski iermeyen sperkritik karbon dioksit (SK-CO2) ektraksiyonundan yararlanlmtr. Ekstraksiyon parametreleri olan karbon dioksit basnc (150-350 bar), scaklk (40-60C) ve yardmc solvent (etanol) konsantrasyonunun (%20-100) toplam antosiyaninlerin eldesi zerine etkileri Box-Behnken modeline gre Yant-Yzey Yntemi ile model oluturularak optimize edilmitir

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.240
Teacher spread0.217 · 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