NYPA/TH!NK Clean Commute Program Final Report - Inception through December 2004
Bibliographic record
Abstract
The Clean Commute Program uses TH!NK city electric vehicles from Ford Motor Company’s electric vehicle group, TH!NK Mobility, to demonstrate the feasibility of using electric transportation in urban applications. Suburban New York City railroad commuters use the TH!NK city vehicles to commute from their private residences to railroad stations, where they catch commuter trains into New York City. Electric vehicle charging infrastructure for the TH!NK city vehicles is located at the commuters’ private residences as well as seven train stations. Ford leased at total of 97 TH!NK city electric vehicles to commuters from Westchester, Putnam, Rockland, Queens, Nassau, and Suffolk counties for $199 per month. First Clean Commute Program vehicle deliveries occurred late in 2001, with data collection commencing in February 2002. Through May, 2004, 24 of the lessees have returned their vehicles to Ford and no longer participate in the Clean Commute Program. Reasons given for leaving the Program include relocation out of the Program area, change in employment status, change in commuting status, and, in a few cases, dissatisfaction with the vehicle. Additionally, 13 vehicles were returned to Ford when the lease was completed. In August 2002, Ford announced that it was ceasing production of the TH!NK city and would not extend any TH!NK city leases. Mileage accumulation dropped in the last quarter of the program as vehicle leases were returned to Ford. The impact of the program overall was significant as participants in the Clean Commute Program drove their vehicles over 406,074 miles, avoiding the use of over 18,887 gallons of gasoline. During the active portion of the program, the TH!NK city vehicles were driven an average of between 180 and 230 miles per month. Over 95% of all trips taken with the TH!NK city vehicles replaced trips previously taken in gasoline vehicles. This report covers the period from Program inception through December 2004.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".