Exploring for the Future program Showcase 2024 - Day 2 National Geoscience theme
Bibliographic record
Abstract
The Exploring for the Future program Showcase 2024 was held on 13-16 August 2024. Day 2 - 14th August talks included: <strong>Session 1 - Architecture of the Australian Tectonic Plate</strong>AusArray: Australian lithosphere imaging from top to bottom - Dr Alexei GorbatovAusLAMP: Mapping lithospheric architecture and reducing exploration space in Australia - Jingming Duan<strong> </strong>Constraining the thermomechanical and geochemical architecture of the Australian mantle: Using combined analyses of xenolith inventories and seismic tomography - Dr Mark Hoggard <strong>Session 2 - Quantitative characterisation of Australia's surface and near surface</strong>AusAEM: The national coverage and sharpening near surface imaging - Dr Anandaroop Ray Unlocking the surface geochemistry of Australia - Phil MainSpotlight on the Heavy Mineral Map of Australia - Dr Alex Walker <br><strong>Session 3 – Maps of Australian geology like never before</strong>An Isotopic Atlas of Australia: Extra dimensions to national maps - Dr Geoff FraserFirst continental layered geological map of Australia - Dr Guillaume SanchezAn integrated 3D layered cover modelling approach:<strong> </strong>Towards open-source data and methodologies for national-scale cover modelling - Sebastian Wong<strong> </strong><br>The recordings will be made available in the coming days.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.395 | 0.180 |
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".