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Record W3197115864 · doi:10.3390/app11177925

Preliminary Valorization of Climatic Conditions Effects on Curing of Air Lime-Based Mortars for Restorative Applications in the Pasargadae and Persepolis World Heritage Sites

2021· article· en· W3197115864 on OpenAlex
Parsa Pahlavan, Stefania Manzi, Hashem Shariatmadar, Maria Chiara Bignozzi

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

VenueApplied Sciences · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory Health
KeywordsCarbonationLimeMortarCuring (chemistry)Environmental scienceDurabilityCalcium carbonateMaterials scienceWaste managementComposite materialMetallurgyEngineering

Abstract

fetched live from OpenAlex

Air lime mortars with addition of two types of sesame cooking oil were synthesized and cured in two different conditions: laboratory and natural climatic conditions of the Pasargadae and Persepolis World Heritage Sites. For the mortars cured in the laboratory, addition of oils in the mortar induced hydrophobic effects, but it adversely affected on permeability values and carbonation rates. However, the air lime mortars cured in the site conditions demonstrated increment in their hydrophobicity and superficial durability without retarding their setting time and adverse effects on their calcium carbonate formation values, due to various climatic parameters existing in natural outdoor conditions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.186

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)0.0000.000

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 head0.026
GPT teacher head0.253
Teacher spread0.227 · 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