Bibliographic record
Abstract
Caffeine is a stimulant compound belonging to the xanthine chemical category that is found in coffee, tea, and cocoa or chocolate (lower diploma), and is protected in many light fluids, as well as in large amounts of energy fluids. Caffeine is a methyl xanthine-type drug used for various purposes, including high-quality breathing in premature babies, pain relief, and combating sleepiness. Caffeine is similar to theophylline and theobromine. Caffeine is used in various cosmetic products and can be administered topically, orally, by inhalation, or by injection. The FDA first approved caffeine citrate injection for apnea of prematurity in 1999. According to a 2017 article, more than 15 million babies worldwide are born prematurely. This corresponds to approximately one to ten births. Early initiation can lead to apnea and pulmonary bronchial dysplasia, a condition that impairs lung development and ultimately causes bronchial allergies or early-onset emphysema in premature infants. Caffeine citrate injections are used to treat apnea of prematurity owing to their effectiveness, safety, and low cost. Caffeine citrate injections are also used to treat postoperative apnea as well as other conditions such as severe hypoxemia, congenital heart defects, obstructive sleep apnea syndrome, and respiratory distress syndrome. Caffeine citrate injections are also used to treat persistent pulmonary hypertension in newborns and seizures due to post-anoxia encephalopathy. Caffeine citrate injections are well tolerated in newborns and infants with few side effects. Common adverse effects include gastrointestinal upset, palpitations, tachycardia, increased blood pressure, restlessness, irritability, and insomnia. In addition, caffeine citrate injections can cause adverse effects such as hyperglycemia, hypocalcemia, hypokalemia, hypomagnesemia, and hypophosphatemia.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.024 |
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".