Bibliographic record
Abstract
Kim Ellis, Director of Earth Space Technology Pty Ltd, is a qualified resource industry research scientist, lawyer and most recently recognised in 2015 as Adjunct Faculty of the International Space University (ISU). Kim’s career in Metals and Mineral Processing Research began with BHP-Billiton and then she was recruited by Rio Tinto Australia for their new Melbourne Research centre at the Latrobe University Technology Park. Returning to work for BHP-Billiton Shortland Research laboratory in New South Wales, Kim worked almost exclusively on the Uranium technology team for Olympic Dam Pilot Plant Process development. When the BHP-Billiton technology team restructured, her work was transferred to the Australian Nuclear Science and Technology Organisation at Lucas Heights with the ANSTO Minerals research team. Her international research project on Asteroid Mining, roadmap and applications was published and presented at the International Astronautical Congress in 2010 and since then Kim has continued to work for the International Space University (ISU) publishing a range of legal and technical papers. The training which Kim has provided for ISU in the last five years, has included workshops on sampling methodology for mining concentrate samples, sample return mission design, legal aspects of mining in space and legal argument for space law cases. In 2014, Kim served as the Department Chair for the Space Policy, Economics and Law in Montreal for the Space Studies Program. An Endeavour Executive Fellow, Kim received an award from the Australian Government Department of Education, Employment and Workplace Relations in 2012 to work based at the NASA Kennedy Space Centre and Florida Institute of Technology in Florida, United States as the deputy academic co-ordinator for the ISU Space Studies Program. Kim believes in ‘giving back’ to her community and is a volunteer scientist with the Australian Government, CSIRO Scientist in Schools program. Here she has ample opportunity to encourage and inspire both primary and high School children in Australia. She speaks regularly about Space Science and Technology for ABC Radio and on numerous television and radio programs both domestically and internationally. Recognised in 2015 as a valued graduate of the University of Newcastle and nominated for the Alumni International Leadership award, Kim was also selected by the University of Western Sydney as an International Law PhD candidate.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.598 | 0.407 |
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".