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Record W3021446800 · doi:10.1113/ep088594

The eye in extreme environments

2020· article· en· W3021446800 on OpenAlexaff

Bibliographic record

VenueExperimental Physiology · 2020
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsSimon Fraser University
FundersJavna Agencija za Raziskovalno Dejavnost RSUniversity of Portsmouth
KeywordsExtreme environmentMechanism (biology)Affect (linguistics)Sensory systemExtreme Cold

Abstract

fetched live from OpenAlex

NEW FINDINGS: What is the topic of this review? This review describes the effect of extreme environments on the visual system. What advances does it highlight? The review highlights the way in which environmental stressors affect the eye and vision, both directly and indirectly. ABSTRACT: Much is known about the physiology and anatomy of the eye. Much less is known about the impact of different environments on the eye, and yet it is the pathophysiology that results from this interaction that is often the precursor to disaster. The present review focuses on the effect of different extreme environments on the visual system; in particular, the way in which such environments affect the sensory mechanism of that system.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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 designBench or experimental
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

Citations17
Published2020
Admission routes1
Has abstractyes

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