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
PURPOSE: To assess the pathogenesis of canalicular lacerations. METHODS: This is a retrospective, clinical case series of 236 patients who sustained a canalicular laceration. All patients who presented to the oculoplastic service of 3 individuals (D.R.J., S.M.G., L.A.M.) from May 1, 1998 to September 30, 2007, with a canalicular laceration were included in the study. Case histories were carefully reviewed in an attempt to classify the mechanism of injury as: "direct (penetrating) injury," "indirect (avulsive)," or "diffuse (avulsive)." Associated injuries (floor fractures, soft tissue lacerations, etc.) were also recorded. RESULTS: Of the 236 patients reviewed, direct canalicular injuries were detected in 128 (54.2%), indirect injuries were detected in 60 (25.4%), and diffuse injuries were detected in 48 (20.3%). Avulsive blunt injuries (due to indirect or diffuse trauma) therefore accounted for 45.7% of the lacerations whereas direct penetrating injuries accounted for 55.2% of the canalicular lacerations. Other injuries associated with the trauma occurred in 152 of the 236 patients (64%). Lacerations involving other portions of the eyelids, periocular area, and face made up the greatest number of associated injuries, and occurred with equal frequency in the direct penetrating group and the indirect/diffuse (avulsive injury) group. Associated injuries more serious in nature including orbital fractures, globe rupture, other body injuries, and head trauma were more commonly seen when diffuse trauma was involved. CONCLUSIONS: Direct, indirect, or diffuse forces may injure canaliculi but direct penetrating injuries were more common than avulsive injuries. More serious injuries (orbital fractures, globe rupture, other body injuries, and head trauma) were more commonly seen when diffuse trauma was involved.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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