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Record W2463602010 · doi:10.1080/01457632.2016.1206390

11th International Conference on Heat Exchanger Fouling and Cleaning—2015, Enfield, Republic of Ireland

2016· article· en· W2463602010 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

VenueHeat Transfer Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFoulingHeat exchangerDesalinationHeat transferMaterials scienceEnvironmental scienceProcess engineeringWaste managementEnvironmental engineeringMechanical engineeringMechanicsChemistryEngineeringMembrane

Abstract

fetched live from OpenAlex

Deposit formation occurs in most chemical, desalination and power generating processes. This is mainly due to the nature of the involved fluids which frequently contain components that may precipitate to form various deposits on heat transfer surfaces. Depending on thickness and thermal conductivity, such deposits can greatly reduce the performance of the apparatus. This widespread phenomenon is associated with significant environmental impact, additional energy consumption leading to 1–2.5% of global CO2 emissions, and reduced production. The cost penalties due to fouling in heat exchanger applications alone have been estimated as about 0.25% of the GDP of industrialized countries.

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)0.000
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 score0.113
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.241
Teacher spread0.216 · 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