Role of vegetation in shaping Early <scp>P</scp>ennsylvanian braided rivers: Architecture of the Boss Point Formation, <scp>A</scp>tlantic <scp>C</scp>anada
Bibliographic record
Abstract
Abstract Vegetation is a major driver of fluvial dynamics in modern rivers, but few facies models incorporate its influence. This article partially fills that gap by documenting the stratigraphy, architecture and palaeobotany of the Lower Pennsylvanian Boss Point Formation of Atlantic Canada, which contains some of the Earth's earliest accumulations of large woody debris. Braided‐fluvial systems occupied channel belts of varied scale within valleys several tens of metres deep and more than 12 km wide, and their deposits predominantly consist of sandy and gravelly bedforms with subordinate accretionary macroforms, high flow‐strength sand sheets and rippled abandonment facies. Discrete accumulations of clastic detritus and woody debris are up to 6 m thick and constitute at least 18% of the in‐channel deposits; they represent lags at the base of large and small channels, fills of minor channels and sandy macroforms that developed in central positions in the upper parts of channel fills. Sandstones with roots and other remnants of in situ vegetation demonstrate that vegetated islands were present, and the abundance of discrete channel fills suggests that the formation represents an anabranching, island‐braided sandbed river, the earliest example documented to date. Although some sphenopsid and lycopsid remains are present, most woody fragments are derived from cordaitalean trees, and the evolution of this group late in the Mississippian is inferred to have exerted a significant influence on fluvial morphodynamic patterns. The formation records a landscape in which active channel belts alternated with well‐drained floodplains colonized by dense, mature forests and local patches of pioneering, disturbance‐tolerant vegetation. Lakes and poorly drained floodplains dominated by carbonate and organic deposition, respectively, were also present. A large supply of woody debris triggered channel blockage and avulsion, and active channel margins and islands within the channel belts were initially colonized by pioneer vegetation and subsequently stabilized by large trees. A similar alternation of stable and unstable conditions is observed in modern braided rivers actively influenced by vegetation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".