Bibliographic record
Abstract
Market Pricing Working Group members have expressed concern that design differences between the Day-Ahead Market (DAM) currently being developed by the IMO and the existing real-time market (RTM) may create systemic price differences between the markets, possibly resulting in and perpetuating inefficient and unfair outcomes and behaviours. Background While day-ahead offers and bids for energy should reflect participants’ expectations of real-time prices, prices between the two markets may nonetheless differ for a variety of reasons, including misestimations made by participants prior to discovering actual real-time conditions, risk averse offer and bid behaviour, varying supply and demand conditions between the markets, market power on the part of physical and/or virtual participants, and market design differences. In other words, day-ahead prices may be biased relative to real-time prices as a consequence of “contextual ” or circumstantial factors (such as the first three factors mentioned above), or may be the result of more systemic factors (such as the last two factors mentioned above). The Market Pricing Working Group has expressed concern with respect to: (a) Whether the proposed Ontario DAM design or RTM is biased relative to the other; and moreover (b) Whether any such bias would be systemic in nature; and (c) Whether any such systemic bias would generate and reinforce inefficient and unfair market outcomes and behaviours. For clarity, efficiency in this context refers to output being produced by the leastcost suppliers, output being consumed by those most willing to pay for it, and the right amount of output being produced. Thus, efficiency relates to the size of
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.744 | 0.604 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".