MétaCan
Menu
Back to cohort

The effect of high pressure treatment on rheological characteristics and colour of mango pulp

2005· article· en· W1975540938 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

VenueInternational Journal of Food Science & Technology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsPulp (tooth)RheologyConsistency indexHigh pressurePulp and paper industryChemistryFood scienceComposite materialMaterials scienceDentistryMedicine

Abstract

fetched live from OpenAlex

Abstract The effect of high-pressure (HP) treatment (100–400 MPa for 15 or 30 min at 20 °C) on the rheological characteristics and colour of fresh and canned mango pulps was evaluated. Differences were observed in the rheological behaviour of fresh and canned mango pulps treated with HP. Shear stress–shear rate data of pulps were well described by the Herschel–Bulkley model. The consistency index (K) of fresh pulp increased with pressure level from 100 to 200 MPa while a steady decrease was noticed for canned pulp. For fresh pulp the flow behaviour index decreased with pressure treatment whereas an increasing trend was observed with canned pulp. Storage and loss moduli of treated fresh pulp with HP increased linearly with angular frequency up to 200 MPa for a treatment time of 30 min while a steady decreasing trend was found for processed pulp. No significant variation in colour was observed during pressure treatment.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.036
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.009
GPT teacher head0.303
Teacher spread0.294 · 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