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Record W4389127600 · doi:10.5151/2594-357x-0008

GEOMETALURGIA DOS FINOS DA USINA DE FÁBRICA

2009· article· pt· W4389127600 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.

Bibliographic record

VenueABM Proceedings · 2009
Typearticle
Languagept
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsImpact
Fundersnot available
KeywordsAnimal scienceChemistryMineralogyBiology

Abstract

fetched live from OpenAlex

PDF | A curva granulométrica da fração abaixo de 0,5 mm apresenta uma forte influência nos valores dos índices de moabilidade do produto pellet feed da Usina de Fábrica. Quanto maior o percentual da fração >0,105 mm, maior o índice de moabilidade e quanto maior o percentual da fração <0,025 mm, menor o índice de moabilidade. Quanto mais elevado o percentual do mineral hematita martítica, maior o índice de moabilidade e com o aumento dos percentuais de hematita lamelar, hematita especular, granular e sinuosa, os índices de moabilidade são menores. Não foram identificadas correlações significativas com o mineral goethita. Quanto mais elevados os valores da perda por calcinação, o índice de moabilidade tende a ser mais elevado. Adquire importância o conhecimento e a influência das variáveis granulométricas, mineralógicas e a perda por calcinação nos índices de moabilidade dos finos de Fábrica, impactando fortemente na produtividade da Usina de Pelotização.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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