MétaCan
Menu
Back to cohort
Record W15826986 · doi:10.1196/annals.1325.031

Autosuffisance céréalière et sécurité alimentaire en Inde : une mise ne perspective historique

2003· dissertation· en· W15826986 on OpenAlexaboutno aff
Virginie Meurier

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2003
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

The differential effects of visual hemifield motion stimulation during fixation of a stationary target were compared under two conditions: fixation straight ahead without any further instructions and fixation straight ahead with attention shifted to the "dark hemifield." Data from nine right-handed volunteers revealed that striate and extrastriate right hemispheric visual areas exhibited larger activations during left hemifield motion stimulation when attention was shifted to the right dark hemifield. Montreal Neurological Institute (MNI) coordinates (26, -98, -4) of the additional clusters activated in the latter condition corresponded best to the kinetic occipital region, which is known to process both shape and motion information, and to parts of area V3 posterior to V3A, which has been shown repeatedly to mediate motion perception. A simple computational model of transhemispheric visuovisual interaction is proposed. The basic mechanism of this model is a central predictor formed by a feedback loop that detects a mismatch between input to the two hemispheres. Predicted stimulation is then compared with the actual input. If the sensed motion of a visual hemifield is larger than the predicted net motion in the model, activation of the respective neural population is increased; conversely, a smaller actual motion causes less activation.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.307
Teacher spread0.264 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207