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Record W2559763510 · doi:10.1017/s0885715616000671

Powder diffraction data for ferrous gluconate

2016· article· en· W2559763510 on OpenAlexafffund
Joel W. Reid

Bibliographic record

VenuePowder Diffraction · 2016
Typearticle
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsCanadian Light Source (Canada)
FundersNational Research Council CanadaWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMonoclinic crystal systemFerrousPowder diffractionMaterials scienceImpurityCrystallographyDiffractionSynchrotronCrystal structureChemistryMetallurgyPhysicsOptics

Abstract

fetched live from OpenAlex

Synchrotron powder diffraction data have been obtained and indexed for ferrous gluconate, a common supplement used for the treatment and prevention of iron-deficiency anemia. Ferrous gluconate (Fe(C 6 H 11 O 7 ) 2 · x H 2 O, Z = 4) crystallizes in a monoclinic cell (space group I 2, #5) with lattice parameters a = 19.953 16(9) Å, b = 5.513 92(3) Å, c = 18.470 58(9) Å, and β = 111.3826(3)°. The pattern shows no evidence of impurity reflections.

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)0.003
metaresearch head score (Gemma)0.004
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.118
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0040.011
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0040.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1180.043

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 head0.046
GPT teacher head0.303
Teacher spread0.257 · 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
GenreDataset

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

Citations6
Published2016
Admission routes2
Has abstractyes

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