Bibliographic record
Abstract
owan Lake is a 700-acre lake about seven miles southwest of Wilmington in Clinton County.The lake was formed in 1950 by damming Cowan Creek.It is the centerpiece of Cowan Lake State Park.The web site at http://www.ohiodnr.com/parks/parkslcowanlk.htm fully describes the location and facilities available.The Delorme map reference is p.77 05.In the spring of 2005 I tried with some success to count the waterfowl on Cowan Lake every day that weather permitted.Cowan Lake is small enough that all the birds on the lake can be counted in six stops along the south shore, accessible from OH 350.Counting usually took about an hour and I tried to time my visits for the last hour before sunset.The waterfowl numbers given below are a summary of those counts.Cowan 's contribution to waterfowl migration was limited by the constraints of open water conditions during the early weeks and by human use when the weather warmed up.Before 15 Feb there was too much ice for the counts to be representative.On the other hand, waterfowl concentrations are very sens itive to human use of the lake.Waterfowl numbers nose-dived with even three or four boats on the lake.After 5 Apr, human traffic on the lake precluded use by more than a handfu l of waterfowl, and most of those were the Canada geese and mallards that breed there.Aggregating the numbers of waterfowl gives a partial picture of the main thrust of waterfowl migration.In Figure I , aggregated numbers are plotted against a linear scale.Plotting the data against a semilog scale, asin Figure 2, gives a better picture of usage.From this chart it is easy to see that during the period there were usually several hundred waterfowl on the lake on days that were conducive to taking data.Note that a zero on this chart indicates that no count was made on that date.From these charts, it is evident that two big pushes occurred, one between 8 Mar and 16 Mar and another between 23 Mar and 31 Mar.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".