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Record W2019439697 · doi:10.3184/095422903782775172

Cadmium adsorption by an organic soil: a comparison of some humic – metal complexation models

2003· article· en· W2019439697 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

VenueChemical Speciation and Bioavailability · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdsorptionChemistryHumic acidIonic strengthCadmiumInorganic chemistryIonic bondingAqueous solutionEnvironmental chemistryIonPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The retention of Cd by an organic soil was investigated as a function of pH and ionic strength. The adsorption of Cd at pH values from 2 to 11 at two ionic strengths (0.053 M and 0.017 M LiNO3) were found to be a function of both pH and ionic strength. Four Cd-humic complexation models were evaluated in order to test the applicability of these models to fit data from batch adsorption experiments. The models varied greatly in their complexity and implicit assumptions. Three were discrete functional group models – a simple diprotic acid model, a two diprotic acid model and the Windermere Humic Aqueous Acid (WHAM) model, and a continuous functional group model - the non-ideal competitive adsorption (NICA) model. The concentration of proton binding sites in the soil was found to be 4.51 mol kg-1. The NICA and WHAM models were more successful than either a simple diprotic acid model or a two diprotic acid model at modeling Cd complexation by the organic soil, although both underestimated adsorption at very high pH values.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.028
GPT teacher head0.259
Teacher spread0.231 · 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