Aeromagnetic map of Mexico: an exploration approach for the new millennium. a progress report
Bibliographic record
Abstract
The integration of the aeromagnetic map of Mexico in a modern, easy-access digital data base is a project supporting as one of its main objectives, successful exploration studies conducted by national and international mining companies searching for new mining prospects. The aeromagnetic map of Mexico is the result of efforts conducted during the last three decades by the Consejo de Recursos Minerales. One short-term objective for this new millennium is to use this data base in other fields of the Earth Sciences. In this way we are looking to contribute to scientific studies of national concern including the establishment of the structure of the earth crust and understanding of geologic processes that gave origin to it. The evaluation of natural resources, delimitation of zones of geologic risk, as well as the solution of environmental problems, will also be beneficed from this data base. One medium term objective is the integration and publication of the magnetic map of North America in cooperation with the geological surveys of Canada and U.S.A. This large-scale map will enable one to study at continental scale the large geologic provinces featuring the northeamerican craton and the accreted terranes to it. This multi-national project will contribute to the geologic understanding at regional scale of the subsurface and its associated natural resources.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".