MétaCan
Menu
Back to cohort
Record W2798178859 · doi:10.6000/1927-5129.2018.14.20

Impact of Cooking Methods on Physicochemical and Sensory Attributes of Apple Gourd

2018· article· en· W2798178859 on OpenAlexvenueno aff
Aamna Soomro, Asadullah Marri, Nida Shaikh, Aijaz Hussain Soomro, Shahzor Gul Khaskheli

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsnot available
Fundersnot available
KeywordsGourdSteamingFood scienceOxalic acidTartaric acidChemistryBoilingCitric acidAcetic acidSensory analysisCooking methodsOrganic chemistry

Abstract

fetched live from OpenAlex

An investigation was carried out to examine the influence of some cooking methods on physicochemical and sensory characteristics of apple gourd during 2016-17. For this purpose, vegetable was procured, washed, peeled, sliced and distributed in five equal lots. Four of these lots were used for individual cooking treatments (i.e. T2=boiling, T3=steaming, T4=frying and T5=microwaving), however, last lot was treated as control (i.e. T1=raw/without treatment). After cooking, all samples were used for analysis. It was found that all organic acids (%) i.e. acetic acid, citric acid, oxalic acid and tartaric acid remained significantly higher (P

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.011
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.428
Teacher spread0.381 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Basic & Applied SciencesSame topicAdvances in Cucurbitaceae ResearchFrench-language works237,207