Ohio's 2006-Lake Erie Charter Fishing Industry
Bibliographic record
Abstract
Abstract Charter fishing provides important angler access to Lake Erie sport fishing and is economically important to local recreational harbor communities. To update information from our 2002 survey, we conducted a mail survey of 517 randomly selected Ohio charter boat captains in early 2007 and received usable information from 249 captains. In 2006, there were 786 Ohio licensed charter guides. This is a decline of 9% from the 861 licensed captains in 2002. Charter firms in 2006 made on average 2.6 more trips per firm (44.7) than in 2002 (42.1). These captains made an estimated 28,563 charter trips in 2006 of which almost 87% were full-day and just over 13% were half-day trips. Charter fishing continues to bring nature-based tourism dollars into local lakefront communities. Our survey data may be used to update the economic impact estimates of this significant sector of the coastal fishing economy.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".