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Record W4413981954 · doi:10.1159/000547382

Besserung der trockenen altersbedingten Makuladegeneration durch Photobiomodulation

2025· article· de· W4413981954 on OpenAlexaff
Lauren Pickel, Alan R. Berger, Nirojini Sivachandran

Bibliographic record

VenueKompass Ophthalmologie · 2025
Typearticle
Languagede
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsSt. Michael's HospitalToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Einleitung: In diesem Fallbericht wird die dramatische Verbesserung des Drusenvolumens und der Sehschärfe bei einem 73-jährigen Patienten beschrieben, bei dem eine trockene altersbedingte Makuladegeneration (AMD) diagnostiziert wurde. Der Patient unterzog sich täglich zu Hause einer Photobiomodulation, in Verbindung mit der Einnahme von AREDS-2-Ergänzungsmitteln. Falldarstellung: Hierbei handelt es sich um die retrospektive Überprüfung einer Falldarstellung aus den Jahren 2023 bis 2024. Nach 8 Monaten kontinuierlicher Photobiomodulationstherapie zu Hause verbesserte sich die Sehschärfe des linken Auges des Patienten von 20/30 auf 20/20, während sie sich beim rechten Auge bei 20/25 stabilisierte. Die äußere Netzhaut wies keine Anzeichen einer geografischen Atrophie auf. Die Gesamtzahl und das Volumen der Drusen waren in beiden Augen deutlich reduziert, links stärker als rechts. Dies wurde durch Querschnittsscans der Makula mittels optischer Kohärenztomografie gezeigt.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.380
Teacher spread0.340 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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