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Record W6992158217

Johnson, Michael oral history interview

2014· other· en· W6992158217 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2014
Typeother
Languageen
FieldMedicine
TopicBiomedical and Chemical Research
Canadian institutionsnot available
Fundersnot available
KeywordsOral historyGovernment (linguistics)Fish <Actinopterygii>George (robot)
DOInot available

Abstract

fetched live from OpenAlex

Michael Johnson is a retired commercial fisherman who has lived in Burnaby and New Westminster his whole life, and had his boat tied up in the Annieville Channel in North Delta. His father was also a fisherman, and Johnson got his introduction to the occupation through his father. At the age of 19, he got his own boat, and called it “The Rocky Way” after the popular song “Rocky Mountain Way” by Joe Walsh. He worked as a commercial fisherman for 25 years, and stopped when the federal government offered him a buyout in the late 1990s. For most of the year, Johnson would fish for salmon in Northern British Columbia (BC) and the average salmon at the time was six pounds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.200
Threshold uncertainty score0.671

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.002
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.2000.035

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.

Opus teacher head0.028
GPT teacher head0.248
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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