Bibliographic record
Abstract
Cigarette Ad } H er toes are pointed.I was told the toes were important.Now her toes are callused and tan in her river ready sandals.She holds a cigarette erect.Now she drinks smoothies full of new age protein powders I can't pronounce.Her eyes are hidden behind thick cat-eye sunglasses.Now her eyes are rimmed with black eyeliner she got tattooed in Mexico.Her mouth is thick and pushed out.Her chin has a dimple, like a forgotten punctuation mark.Now her mouth is a light pink sagging line, her chin is a cobweb of fine wrinkles.The background could be the skyline of Hollywood or some suburb of New York City.Now she lives in Mexico or in her too-silver airstream at the Missoula KOA.I lay this picture over how I know her today.The effect is harsh and uncomfortable like silk over burlap.Posed in a plastic woven lounge chair, hair styled, cigarette perched and ready, pedicured toes, plaid shorts melt into pale long legs, her white collared shirt wrinkled at the elbows, the buttons cast an S shaped shadow down her chest."Is that the aunt that looks like your mom?" is the way she is identified among my friends.I know her from the others as the one who likes potatoes as much as I do.She is the aunt who never did art projects with me or sent crocheted bears.She is the aunt who takes me hiking and on driving trips to ponds during family reunions.Buddhism, literature, travel, and trees are the things we talk about.The aunt whose husband's ashes I freed into the Blackfoot and toasted with my first Canadian Crown Royal Whiskey on the rocks.Like my mother and me, when she laughs her cheeks rise and almost cover her squinted eyes.Her visits from Mexico are not few, but when I see her it seems like years have passed.Posed on the lawn chair she is exotic and familiar to me.A necklace of power lines runs above her head.The front left corner of the lounge chair is cut off.Her white legs are over exposed.The depth of field is wrong.The mountains are both-78
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.904 | 0.809 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".