Cyclostratigraphy and paleoenvironmental inference from downhole logging of sediments in tropical Lake Towuti, Indonesia
Bibliographic record
Abstract
Abstract Lake Towuti is located on central Sulawesi/Indonesia, within the Indo Pacific Warm Pool, a globally important region for atmospheric heat and moisture budgets. In 2015 the Towuti Drilling Project recovered more than 1000 m of drill core from the lake, along with downhole geophysical logging data from two drilling sites. The cores constitute the longest continuous lacustrine sediment succession from the Indo Pacific Warm Pool. We combined lithological descriptions with borehole logging data and used multivariate statistics to better understand the cyclic sequence, paleoenvironments, and geochronology of these sediments. Accurate chronologies are crucial to analyze and interpret paleoclimate records. Astronomical tuning can help build age-depth models and fill gaps between age control points. Cyclostratigraphic investigations were conducted on a downhole magnetic susceptibility log from the lacustrine facies (10–98 m below lake floor) from a continuous record of sediments in Lake Towuti. This study provides insights into the sedimentary history of the basin between radiometric ages derived from dating a tephra layer (~ 797 ka) and C 14 -ages (~ 45 ka) in the cores. We derived an age model that spans from late marine isotope stage (MIS) 23 to late MIS 6 (903 ± 11 to 131 ± 67 ka). Although uncertainties caused by the relatively short record and the small differences in the physical properties of sediments limited the efficacy of our approach, we suggest that eccentricity cycles and/or global glacial-interglacial climate variability were the main drivers of local variations in hydroclimate in central Indonesia. We generated the first nearly complete age-depth model for the lacustrine facies of Lake Towuti and examined the potential of geophysical downhole logging for time estimation and lithological description. Future lake drilling projects will benefit from this approach, since logging data are available just after the drilling campaign, whereas core descriptions, though more resolved, only become available months to years later.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".