Bibliographic record
Abstract
The clock's blue glows 4:38 AM through fluttering lashes.A moth to a flame.I stare blankly; lucid with exhaustion.Parsing through fractured pieces of dreams and vague recollections, whispers inside an empty space with no walls to place them.No time to face them.My patient.Why is he so sick?Heart failure?Did he get enough Lasix?It haunts me.It follows me.It plagues me.The damp sweat on my backside makes my clothes cling tightly.A child's hand clasped inside his mother's palm.Desperate but welcomed.It's just COVID-19.It has to be.The layers are peeled off one by one, shedding the message of torment.Slowly.Pneumonia?It's been five days of antibiotics already.4:52 AM A blunt deluge of water batters my face in a shower stall colder than I expect.A blanket of pine needles hits me.My skin jolts at every edge.Am I awake now?What if it's a pulmonary embolus?No. It's just COVID-19.It has to be. EEyes closed Abdu Sharkawy 21
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.596 | 0.304 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".