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Impactos das mudanças climáticas no zoneamento agroclimatológico do café arábica no Espírito Santo

2016· article· pt· W2414972494 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRevista Agro mbiente On-line · 2016
Typearticle
Languagept
FieldEnvironmental Science
TopicRural Development and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsHadCM3Environmental scienceClimatologyAtmospheric sciencesGCM transcription factorsClimate changeGeologyGeneral Circulation Model

Abstract

fetched live from OpenAlex

Objetivou-se com este trabalho definir, por meio do zoneamento agroclimatológico atual e para os próximos 100 anos, áreas com diferentes aptidões climáticas para a cultura do café arábica (Coffea arabica L.), no estado do Espírito Santo. Para isso, foram utilizados dados de temperatura média do ar e precipitação pluviométrica, em escala mensal e anual, de séries históricas representativas do período de 1976 a 2006. Foi necessário simular o efeito do incremento de temperatura de +1ºC, +2ºC, +3ºC, +4ºC e +5ºC, por meio da média obtida do resultado de seis modelos, a saber: GFDL-R30 (Geophysical Fluid Dynamics Laboratory, R-30 resolution model), CCSR/NIES (Center for Climate Research Studies Model), CSIROMk2 (Common wealth Scientific and Industrial Research Organization GCM mark 2), CGCM2 (Canadian Global Coupled Model version 2), ECHAM4 (European Centre Hamburg Model version 4) e HadCM3 (Hadley Centre Coupled Model version 3). Os resultados encontrados demonstraram que, atualmente, as áreas completamente aptas representam 19,49%, e com acréscimo de 5°C diminuirá para 0,02%, enquanto as áreas completamente inaptas passarão de 33,47% para 95,63% do território do Espírito Santo, tornando o café arábica impróprio para o cultivo no estado, se mantidas as características genéticas e fisiológicas que tem como limite de tolerância de temperaturas médias anuais entre 23°C e 24°C.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.067

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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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