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Record W2908535954 · doi:10.1177/0967033518821834

Using near infrared measurements to evaluate NaCl and KCl in water

2019· article· en· W2908535954 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Near Infrared Spectroscopy · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical and Physical Studies
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaMosaic Company
KeywordsSaturation (graph theory)AbsorbanceAqueous solutionSalinityAnalytical Chemistry (journal)ChemistryLinearityInfraredEnvironmental chemistryChromatographyMathematicsOpticsPhysicsPhysical chemistryGeology

Abstract

fetched live from OpenAlex

Spectral differences between aqueous solutions of NaCl and KCl have received minimal attention in previous research due to strong similarities between the two salts and the lack of motivation to differentiate between them. Correlations between salinity and absorbance have been developed previously with varying degrees of linearity but have not been tested to saturation. This work will demonstrate that correlating spectral measurements and the concentration of NaCl and KCl in water can be extended up to the saturation point of both salts and that solutions of these salts with unknown concentrations can be distinguished. Spectral data for samples of NaCl and KCl in single-salt solutions were collected up to saturation and correlations were developed for differentiating between solutions of the two species. These correlations were able to correctly identify the solution type for all solutions in the test set and estimate their concentrations with an average error of 0.9%.

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 score0.014
Threshold uncertainty score0.421

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 head0.031
GPT teacher head0.305
Teacher spread0.275 · 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