Bibliographic record
Abstract
The Mary Ann Morris Animal Society (M.A.M.A.S.) is a canine adoption operation that originated with a group of animal lovers in sparsely populated Bamberg County, South Carolina, which, for reasons I will go into below, has found itself perennially awash in stray dogs. Around 2000, the members of this group partnered with the county government to build a permanent animal shelter and develop an adoption pipeline to the populous Mid-Atlantic and Northeast regions of the United States. The transport wing of the organization, M.A.M.A.S. On The Move, ferries dogs up the Interstate Highway 95 corridor, which begins in Miami, Florida, and runs all the way to Maine's border with Canada. Through adoption websites and the conscientious work of a phalanx of volunteers fanned out over the Eastern Seaboard, these northering rescue dogs find their “forever homes” in and around metropolises such as Washington, DC, Baltimore, Philadelphia, and New York City. My wife and I, who live in Baltimore, owe to the coordinated efforts of M.A.M.A.S. rescuers and transporters our dogs Cecil and Cassius, who, although they came from different litters and were adopted a year apart, were each found abandoned along Bamberg County's rural roads.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.161 | 0.092 |
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".