MétaCan
Menu
Back to cohort
Record W6991265148

Galling insect distribution on psychotria barbiflora (rubiaceae) in a fragment of atlantic forest

2009· other· es· W6991265148 on OpenAlexfundno aff

Bibliographic record

VenueActualidad Contable FACES · 2009
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
FundersUniversité de Sherbrooke
KeywordsCecidomyiidaeFloristicsDistribution (mathematics)PsychotriaInflorescenceHabit
DOInot available

Abstract

fetched live from OpenAlex

Se estudió la distribución de un Cecidomyiidae formador de agallas en las hojas, individuos y poblaciones de Psychotria barbiflora (Rubiaceae) en un fragmento de un bosque atlántico en Usina Serra Grande, Alagoas, Brasil. Se colectaron 345 hojas para caracterizar las agallas y analizar su patrón de distribución. El número de agallas por hoja infectada varió entre 1 y 100. La oviposición del insecto se produjo sobre las venas de la hoja en la región basal de la epidermis abaxial. El cecidomyiidae pareció preferir las hojas jóvenes ubicadas en el ápice de los brotes. El número total de hojas se correlacionó positivamente con la altura de las plantas, en tanto que el daño individual de las hojas se correlacionó negativamente, demostrando que la complejidad de los aglomerados y la densidad no afectan la tasa de ataque del insecto formador de agallas. De 213 plantas evaluadas, 93 tenían agallas (43.7%). La densidad espacial de la planta hospedera no afectó el daño individual de la hoja. El patrón observado de la distribución de agallas pudo ser debido a las estrategias del insecto para optimizar la nutrición de las agallas.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.270
Teacher spread0.247 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueActualidad Contable FACESFrench-language works237,207