SupplementaryMaterial_Santos-et-al_2023
Bibliographic record
Abstract
SUPLEMENTARY MATERIAL Title: An in-house X-ray fluorescence spectrometer development for in vivo analysis of plants" Authors: Eduardo Santos1,6, Jonatha Demetrio Gozetto2, Eduardo de Almeida1, Marcos Augusto Stolf Brasil3, Nicolas Gustavo da Cruz da Silva1,3, Vinicius Pires Rezende1, Higor José Freitas Alves da Silva1, Julia Rosatto Brandão1, Gabriel Sgarbiero Montanha1,4, José Lavres1, Hudson Wallace Pereira de Carvalho1,5 Institutional Affiliations: 1 Group of Specialty Fertilizers and Plant Nutrition, Centre for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, Brazil; 2 FIBRAMEC, Piracicaba, Brazil; 3 Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil; 4 Laboratory of Functional Genomics and Proteomics of Model Systems, Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy; 5 Chair of Soil Science, Mohammed VI Polytechnic University, Lot 660, Ben Guerir 43150, Morocco; 6 Department of Plant Sciences, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada Description: pdf-format file containing detailed information regarding the general mechanical features of an in-house XRF spectrometer, named SIPA, focused on in vivo analysis of plant materials. The reuse of the material is allowed upon proper citation.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.925 | 0.671 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".