Bibliographic record
Abstract
He's back home again.In Italy.His beloved Alps.He's been gone a couple of weeks now.The first few days were fine.I caught up on everything around here.It actually felt good.Calming.I ate when I felt like it, did what I wanted.Not that I have to cater to him when he's here.I just do.I find it hard not to.Even when my friends find fault.I must have some sort of addiction.I think of people who try to quit smoking or conquer a drug habit.There are step by step programs that are supposed to liberate you from your self destructive practices.I think perhaps I too am in need of some such program.But, I must admit, it is liberating to be able to do as I please right now.I guess I'll call this stage one: the liberating stage.Next, I think, comes the anticipation stage which is when I can think about all I'll accomplish now that I'm alone.Like plucking and trimming my eyebrows, for instance.If I don't tend to them soon, I'll need a weedwacker to get them under control.But it's starting already.That feeling of being abandoned.While he's cavorting in the Alps, I'm here doing my duty.Resentment is looming ahead like a thief casing a home, stalking me.I know I'm vulnerable.I know it isn't really true I can do as I please.I have to cut the grass, pullthe weeds, check the mail, pay the bills, take the dog for a walk, eat, sleep.And today I have to go down to our cottage to mow out there too.And it's June Bug season and I need to slap those pesky critters off the house.I bet the place is swarming with the darned things.There'll be clouds of them buzzing about sounding like a zillion miniature airplanes.Who says it's quiet by the lake?This time of year, it's like having that ear ringing disease.Tinnitus, is it?KKK Yes, the first few days are always fine.Liberation, exhilaration and anticipation.Free at last.And that's quickly followed by the accomplishment
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.140 | 0.061 |
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".