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Record W2016480975 · doi:10.1115/sbc2008-192576

Mechanics of Individual-Specific Corneoscleral Shell Models

2008· article· en· W2016480975 on OpenAlexaff
Richard Norman, Ian A. Sigal, Sophie Rausch, Inka Tertinegg, Armin Eilaghi, Sharon Portnoy, John G. Sled, John G. Flanagan, C. Ross Ethier

Bibliographic record

VenueASME 2008 Summer Bioengineering Conference, Parts A and B · 2008
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsGlaucomaOptic nerveOptic neuropathyLaminaMedicineEtiologyBlindnessOphthalmologyIschemiaPathologyOptometryAnatomyInternal medicine

Abstract

fetched live from OpenAlex

Glaucoma is a group of diseases involving a progressive optic neuropathy of unknown etiology. It is one of the leading causes of blindness worldwide. It has been postulated that glaucomatous optic neuropathy may result from mechanical stresses on the optic nerve fibers passing through the lamina cribrosa (LC), from ischemia in the LC region, or from a combination of these two.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.052
GPT teacher head0.235
Teacher spread0.182 · 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 designSimulation or modeling
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
Published2008
Admission routes1
Has abstractyes

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Same venueASME 2008 Summer Bioengineering Conference, Parts A and BSame topicGlaucoma and retinal disordersFrench-language works237,207