The fault in our TARs: A critical review of research paradigms for intermediate‐scale bedforms on Mars
Bibliographic record
Abstract
Abstract We provide a critical review of research paradigms for classifying intermediate‐scale aeolian bedforms on Mars and the new terminology that has emerged. The systematic classification of bedforms has always been challenging and debated, and no paradigmatic knowledge organization system exists beyond general agreement on the importance of a distinction between ripples and dunes. The diverse aeolian landscapes of Mars have introduced further topics and challenges to these debates. We argue that Martian aeolian geomorphology's knowledge organization system for intermediate‐scale bedforms is preparadigmatic and that consensus over terminology and their definitions has not been established in the literature. A preparadigmatic science can be functional only if scientists operating in the discipline provide precise, falsifiable definitions or use abductive logic. Drawing on evidence and examples from the literature, we argue that the replacement of the conventional abductive paradigm used in bedform classification with inductive logic has created an emerging disciplinary paradigm based on scientific hesitancy and a dependence on complex inductive research structures, epitomized by the concepts of ‘transverse aeolian ridges’ (TARs) and ‘large Martian ripples’ (LMRs). We show that TAR and, increasingly, LMR are inductive constructs that have been popularized despite them causing significant confusion. Notably, we highlight how the terms are irreconcilably used as both a class of bedform and as a non‐genetic placeholder term for bedforms. Suggestions for moving beyond the need for TAR and LMR are provided, focusing on a return to more direct and local hypothesis‐driven research inspired by W.M. Davis's notion of outrageous geological hypotheses. Recent debate surrounding bedforms in Gale crater is presented as an example of the productivity of such an approach, and it is recommended that TAR and LMR no longer be used.
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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 | 0.034 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.023 | 0.012 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".