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Record W4382722627 · doi:10.14740/jmc4093

Identifying the Cause of Acute Left-Sided Visual Loss: A Clinical Dilemma

2023· article· en· W4382722627 on OpenAlexvenueno aff
Anirudh R. Damughatla, Vanessa Milan-Ortiz, Pragna Koleti, Myrna M. Milan-Ortiz, Sudhir Pasham, Abhishek R. Damughatla, Saivaishnavi Kamatham, Kareem Bazzy

Bibliographic record

VenueJournal of Medical Cases · 2023
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHead and neckEtiologyHead and neck cancerRadiation therapyThrombusCancerIncidence (geometry)Intensive care medicineLeft ventricular thrombusSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Given the global increase in the incidence of head and neck cancers over the last decade, the use of chemoradiation has also increased. It is well known that chemotherapy/radiation are established standard therapies in head and neck cancers, especially in patients who are not candidates for surgery. Despite this increase in chemoradiation therapies in head and neck cancers, there is a lack of established guidelines on the surveillance and screening of these patients for long-term complications. We present an interesting case of acute left eye blindness in a veteran patient with a history of laryngeal cancer status post chemoradiation and in the setting of a left ventricular (LV) thrombus on anticoagulation resulting in a diagnostic challenge determining the etiology. This case emphasizes the need for thorough patient-centered annual evaluation, thus providing an opportunity for early noninvasive or minimally invasive intervention.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.003
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0020.001

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 head0.134
GPT teacher head0.468
Teacher spread0.333 · 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 designCase report
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
Published2023
Admission routes1
Has abstractyes

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