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Record W4384212340 · doi:10.7202/1098431ar

Sementes da Terra

2023· article· pt· W4384212340 on OpenAlexvenueno aff
Kowawa Kapukaja Apurinã

Bibliographic record

VenueSens public · 2023
Typearticle
Languagept
FieldArts and Humanities
TopicAmazonian Archaeology and Ethnohistory
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyBiologyPhilosophy

Abstract

fetched live from OpenAlex

“As sementes do mundo são espalhadas pela bondade dos seres vivos, dos bichos, dos ventos, da água”. Assim inicia a intervenção da antropóloga e ativista indígena Kowawa Kapukaja Apurinã. Sob a forma de ensaio realizado no ambiente da floresta, e por meio de um relato sensível e engajado, Kowawa nos guia para uma reflexão sobre nós mesmos. “Quais sementes espalhamos pelo mundo?”, ela indaga. Seu convite nos leva a olhar para as nossas próprias humanidades como inseridas em um cosmos que vai além de nossa existência: universo, rio, plantas e árvores, também somos sementes nesse sistema.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.012
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.083
GPT teacher head0.269
Teacher spread0.186 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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