Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A standard approach to the diagnosis of dry eye disease across eye care practitioners is critical to reassuring the patient, providing consistency between practitioners and informing governments as to the true prevalence and resulting healthcare needs. The Tear Film & Ocular Surface Society (TFOS) Dry Eye Workshop (DEWS) III has reviewed the evidence-base since their previous reports published in 2017 and revised the definition to "Dry eye is a multifactorial, symptomatic disease characterized by a loss of homeostasis of the tear film and/or ocular surface, in which tear film instability and hyperosmolarity, ocular surface inflammation and damage, and neurosensory abnormalities are etiological factors." Key features from the definition include that dry eye disease is multifactorial, is a disease and not a syndrome and is always symptomatic. Differential diagnosis and ocular examination guidance is given along with the risk factors that should be discussed with the patient. The recommended screening questionnaire is the OSDI-6 with a cut-off score ≥4. A positive result together with a non-invasive breakup time <10s or alternatively tear film hyperosmolarity (≥308mOsm/L in either eye or an interocular difference >8mOsm/L) or alternatively >5 corneal fluorescein and/or >9 conjunctival lissamine green punctate spots and/or lid margin lissamine green staining of ≥2mm length & ≥25 % width, gives a diagnosis of dry eye. Subclassification was separated into tear film deficiencies (lipid, aqueous and mucin/glycocalyx), eyelid anomalies (blink/lid closure and lid margin) and ocular surface abnormalities (anatomical misalignment, neural dysfunction, ocular surface cell damage/disruption and primary inflammation/oxidative stress) components, with appropriate clinical tests and cut-offs provided to identify these etiological drivers in an individual, to inform appropriate management and therapy.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it