Bibliographic record
Abstract
bathymetry of lake ontario has been compiled as a component of a noaa project to rescue great lakes lake floor geological and geophysical data and make it more accessible to the public the project is a cooperative effort between investigators at the noaa national geophysical data center s marine geology geophysics division ngdc mgg and the noaa great lakes environmental research laboratory glerl was compiled utilizing the entire historic sounding data base the entire historic hydrographic sounding data base from the u s and canada originally collected for nautical charting purposes was used to create a complete and accurate representation of lake ontario bathymetry the u s data primarily came from the nos hydrographic survey data this and other bathymetric sounding data collected by the u s national ocean service s nos coast survey and the u s army corps of engineers was employed to construct bathymetric contours at 1 meter intervals from 1 10 meters depth and 2 meter intervals at depths greater than 10 meters compilation scales ranged from 1 10 000 to 1 50 000 bathymetric sounding data collected by the canadian hydrographic service chs were employed to construct bathymetric contours at 1 meter intervals and compilation scales ranging from 1 1 000 to 1 30 000 digitization of the bathymetric contours merging of the bathymetric contour data sets poster construction and preparation of a cd rom were accomplished at the ngdc multibeam bathymetric data collected by the university of new brunswick s ocean mapping group unb omg with support of the geological survey of canada gsc and the chs were kindly made available in gridded form in the two areas where multibeam bathymetric data were available no other bathymetric data were used in the compilations in some areas all available canadian and u s bathymetric sounding data collected at different times on different survey expeditions were used to derive the contours the u s coastline used was primarily the glerl medium resolution vector shoreline dataset lee 1998 where needed for more coverage the nos medium resolution vector shoreline for the conterminous u s 1994 dataset was used coastlines from the chs bathymetric sounding data field sheets were used to complete the canadian coastline images were constructed using the publicly available software generic mapping tools gmt
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".