Bibliographic record
Abstract
My son, Daniel (Figure 1), is entering grade 2 this year and as we head out in late August with the school's list of supplies he'll require, I make a few notes for additional items that he'll need. Daniel is thrilled to see that we need a large box of sugary fruit snacks to treat low blood sugar at school. He's not so delighted about the fresh box of keto-sticks we need, but he learned long ago that there is no point worrying about all this ‘stuff’. We're nearing the end of Daniel's third year with type 1 diabetes and I'm not sure he remembers much about the life before finger pokes and injections. Daniel on his way to school Daniel on his way to school I've become gradually more comfortable with the idea of sending him off to school. It's a bit of a leap of faith believing that strangers, in conjunction with a six-year-old boy, can cope with this chronic condition for 6 h a day. But I've done everything I can think of to prepare both Daniel and the school staff for this responsibility. My biggest fear when I say goodbye to Daniel each morning will be that he will have a severely low blood sugar. If Daniel plays extra hard at recess or doesn't finish eating, his blood sugar can drop quickly. Along with high and low blood sugars, a second concern is the effect of those blood sugar extremes on Daniel's ability to concentrate at school. Finally, I want to ensure that Daniel doesn't feel too different from other kids. I don't want his diabetes to define him. I want him to go to birthday parties (and eat cake!). To counter our concerns, my husband and I have tried to make Daniel as independent as possible. He has always been able to check his own blood sugar. We ensure he has a fruit leather in his pocket each morning. He knows more about diabetes than most of the grown-ups around him so we instruct him to eat the sugar in his pocket when he feels low, even if adults tell him he can't eat now. We are fortunate that he generally knows when he is feeling low and rarely gets it wrong. Daniel is the only child at his school with type 1 diabetes. When kindergarten began, I anxiously reviewed all the back-to-school materials provided by the Alberta Children's Hospital and the Canadian Diabetes Association. I completed a detailed form with information specific to Daniel, including targets for blood sugar, symptoms and treatment of high and low blood sugar, a photograph ofDaniel and when to contact me. Each year, I meet with Daniel's teacher before the start of the school year and go through the materials. The information is posted in the classroom and the staff room. When Daniel started grade 1 and would be encountering more teachers and staff, the school nurse did a lunch presentation to educate the rest of the staff about type 1 diabetes. I rest easier knowing that the staff will know what to do in an emergency. Thankfully, there have been no emergencies. The teachers and staff go out of their way to make my son's experiences at school safe, educational and enjoyable. One afternoon, when Daniel was getting low, one of the teachers sat down with him at the little table in the back of the classroom and shared her orange with him. He came home beaming about how they “treat him like a king around there”. It just doesn't get much better than that. (Well, a cure would be nice, but that's a topic for another day!)
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".