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Record W4411347370 · doi:10.1007/978-1-0716-4646-5

Food Waste Valorization

2025· book· en· W4411347370 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMethods and protocols in food science · 2025
Typebook
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsnot available
FundersDirectorate for Biological SciencesGovernment College University, LahoreAdama Science and Technology UniversityUniversidad Arturo PratUniversity of GujratUniversitat de LleidaUniversity of Agriculture, FaisalabadIndian Institute of Technology DelhiBacha Khan UniversityUniversity of TehranShiraz UniversityUniversiti Putra MalaysiaUniversità degli Studi di SassariConsorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei MaterialiUniversity of GalwayNova Southeastern UniversityJSS Academy of Higher Education and ResearchAdamas UniversityKarpagam Academy of Higher EducationGlasgow Caledonian UniversityUniversità degli Studi di MilanoSRM Institute of Science and TechnologyRowan UniversityUniversidad de SevillaUniversity of CalcuttaIstanbul Teknik ÜniversitesiUniversity of MinnesotaDepartment of Bioproducts and Biosystems Engineering, University of MinnesotaMcGill UniversityUniversità degli Studi di Napoli Federico II
KeywordsFood wasteWaste managementEnvironmental scienceBusinessPulp and paper industryEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.979
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.058
GPT teacher head0.375
Teacher spread0.317 · 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