R<scp>obert</scp> J<scp>ohn</scp> G<scp>ibson</scp>
Bibliographic record
Abstract
John Gibson was born into an Anglo‐Irish military family in India. With the onset of WWII, he was sent back to England where he attended St. Peter's public school in York. He went on to Trinity College, Dublin, where it was expected he would study medicine. But he wanted to study fisheries, an impossibility in Ireland at the time, so in 1958 he crossed the ocean and landed at the Atlantic Biological Station in St. Andrews, New Brunswick. After obtaining a master's at the University of Western Ontario (1965), he worked in Manitoba for five years before completing a Ph.D. at the University of Waterloo (1973). The Woods Hole Oceanographic Institution hired Gibson to conduct salmon research and direct their freshwater field station at the mouth of the Matamek River in Quebec. He left Woods Hole in 1978 and in 1980 became a senior research scientist at the Department of Fisheries and Oceans (DFO) in St John's, Newfoundland. Wherever Gibson went, a stream tank followed. He built one on the bank of the Matamek River beside one of the falls, one in a lab at Woods Hole, and then one at DFO in St John's.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.400 | 0.171 |
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".