Deductive model proposed for evaluating terrestrial analogues
Bibliographic record
Abstract
Analogical science is science in absentia. Devoid of direct evidence or data sufficient to explain the physical and biochemical processes shaping Mars, Europa, and other non‐terrestrial bodies, planetary scientists seek insight by referring to Earth‐based analogues [Stone, 1999]. This means searching for a terrestrial source mirroring conditions of a non‐terrestrial target, explaining activity at the target in terms of a theory extrapolated from the source, and then seeking observable evidence at the target to confirm analogical viability. An apt or meaningful analogy narrows the conceptual space between source and target, enabling the scientist to enhance his understanding of a distant target by studying a source closer at hand. Heretofore, there have been no clear rules or general criteria with which to evaluate the aptness or meaningfulness of an interplanetary analogy or terrestrial analogue. To redress this shortcomings three‐rung empirically derived model is proposed.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".