Bibliographic record
Abstract
Memorializes Martha Helson Wilson (1929-2020), a physiological psychologist. Martha enrolled at Yale University for doctoral study in 1952, where she studied the physiological aspects of sensation with Burton Rosner. She also developed skills in electrophysiology under the direction of Karl Pribram, who became her career-long mentor, collaborator, and friend. In Pribram's Laboratory of Neurophysiology at the Institute of Living in Hartford, Connecticut, Martha met William A. Wilson, another lifelong collaborator as well as her husband for 62 years. Her behavioral investigations of intersensory learning were mainstream comparative psychology, as were her innovative studies of category learning that bridged animal research and human clinical neuropsychology, a field Wilson entered via her 1979 sabbatical with Brenda Milner at the Montreal Neurological Institute. Martha Wilson used this broad knowledge and experience to lead APA Division 6 (Physiological and Comparative Psychology)as its secretary-treasurer, executive committee member-at-large, representative to the Council of Representatives, president-elect, president (1986 -1987), and past president. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.036 |
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".