Bibliographic record
Abstract
to Science Four Years After the 2004 Indian Ocean Tsunami, Part II: Observation and Data Analysis.- Field Survey and Geological Effects of the 15 November 2006 Kuril Tsunami in the Middle Kuril Islands.- The November 15, 2006 Kuril Islands-Generated Tsunami in Crescent City, California.- Validation and Joint Inversion of Teleseismic Waveforms for Earthquake Source Models Using Deep Ocean Bottom Pressure Records: A Case Study of the 2006 Kuril Megathrust Earthquake.- Variable Tsunami Sources and Seismic Gaps in the Southernmost Kuril Trench: A Review.- In situ Measurements of Tide Gauge Response and Corrections of Tsunami Waveforms from the Niigataken Chuetsu-oki Earthquake in 2007.- Excitation of Resonant Modes along the Japanese Coast by the 1993 and 1983 Tsunamis in the Japan Sea.- Numerical Study of Tsunami Generated by Multiple Submarine Slope Failures in Resurrection Bay, Alaska, during the M w 9.2 1964 Earthquake.- Lituya Bay Landslide Impact Generated Mega-Tsunami 50th Anniversary.- Tsunamis on the Pacific Coast of Canada Recorded in 1994-2007.- The 15 August 2007 Peru Earthquake and Tsunami: Influence of the Source Characteristics on the Tsunami Heights.- Tide Gauge Observations of 2004-2007 Indian Ocean tsunamis from Sri Lanka and Western Australia.- Reconstruction of Tsunami Inland Propagation on December 26, 2004 in Banda Aceh, Indonesia, through Field Investigations.- The 1856 Tsunami of Djidjelli (Eastern Algeria): Seismotectonics, Modelling and Hazard Implications for the Algerian Coast.- Analysis of Observed and Predicted Tsunami Travel Times for the Pacific and Indian Oceans.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.115 | 0.075 |
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".