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Record W2927296053 · doi:10.4995/ids2018.2018.8877

Proceedings of 21th International Drying Symposium

2018· paratext· en· W2927296053 on OpenAlexaboutno aff
Juan A. Cárcel, G. Clemente, J.V. García‐Pérez, A. Mulet, Carmen Rosselló

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsExposition (narrative)Event (particle physics)Library scienceEngineeringComputer scienceEngineering managementOperations researchManagementArt

Abstract

fetched live from OpenAlex

The institutional organizers of IDS 2018 are the Department of Food Technology at the Universitat Politècnica de València and the Department of Chemistry at the University of Illes Balears. Like its previous biannual IDS conferences, the objective of 21th IDS is to provide the most advanced and comprehensive global forum for disseminating results and data in research, development, and applications in drying/dewatering sciences and technologies. This Symposium will be held in the main campus of the Universitat Politècnica de València and aims to bring together leading researchers and engineers from academia and from industry from all around the world in this university environment. It is also planned during the meeting an exposition of industrial equipment and developments. An Award program will be also part of the event for the international drying community. This Symposium is the 21th event in the series founded by Professor Arun S. Mujumdar at McGill University, Montreal, Canada, in 1978.

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)0.002
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.199
Threshold uncertainty score0.667

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1990.084

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 head0.238
Teacher spread0.215 · 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
GenreOther

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

Citations183
Published2018
Admission routes1
Has abstractyes

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