The Lab

Autoresearch loop: overnight batches run experiments, keep winners, discard losers. Edit program.md files to steer what gets tried next.

Total Experiments

72

Kept

57

79.2% keep rate

Tiers Active

8

of 9

Best Model

persistence

Experiment Timeline (Metric by Tier)

Win Rate by Tier

Model Leaderboard

RankModelISOMAPECountStatus
1persistenceERCOT0.00%15Production
2persistenceNYISO0.10%281Production
3rolling_avg_24hNYISO0.21%287Challenger
4same_hour_yesterdayNYISO0.25%285Challenger
5rolling_avg_24hERCOT0.53%15Challenger
6rolling_avg_24hSPP2.50%38Challenger
7same_hour_yesterdaySPP4.05%40Challenger
8persistenceSPP5.08%39Production

Recent Experiments

Click a row to view details

ModuleTierISOMetricDeltaKeptWhen
loop7-weather-features
feature-extraction
ISO_NE0.1840+0.1840Yes50d ago
loop7-weather-features
feature-extraction
ISO_NE0.00000.0000Yes50d ago
loop7-weather-features
feature-extraction
ISO_NE24.3600+24.3600Yes50d ago
loop7-weather-features
feature-extraction
PJM0.00000.0000Yes50d ago
loop7-weather-features
feature-extraction
PJM22.3300+22.3300Yes50d ago
loop7-weather-features
feature-extraction
MISO0.0080+0.0080Yes50d ago
loop7-weather-features
feature-extraction
MISO0.3100+0.3100Yes50d ago
loop7-weather-features
feature-extraction
MISO0.00000.0000Yes50d ago
loop7-weather-features
feature-extraction
MISO26.5800+26.5800Yes50d ago
loop7-weather-features
feature-extraction
ERCOT0.0180+0.0180Yes50d ago
loop7-weather-features
feature-extraction
ERCOT0.3520+0.3520Yes50d ago
loop7-weather-features
feature-extraction
ERCOT4.2900+4.2900Yes50d ago
loop7-weather-features
feature-extraction
ERCOT3.2600+3.2600Yes50d ago
loop7-weather-features
feature-extraction
SPP0.1740+0.1740Yes50d ago
loop7-weather-features
feature-extraction
SPP0.2640+0.2640Yes50d ago
loop7-weather-features
feature-extraction
SPP2.9400+2.9400Yes50d ago
loop7-weather-features
feature-extraction
PJM0.3730+0.3730Yes50d ago
loop7-weather-features
feature-extraction
SPP10.3300+10.3300Yes50d ago
loop7-weather-features
feature-extraction
CAISO0.0120+0.0120Yes50d ago
loop7-weather-features
feature-extraction
CAISO0.2570+0.2570Yes50d ago
loop7-weather-features
feature-extraction
PJM0.0200+0.0200Yes50d ago
loop7-weather-features
feature-extraction
CAISO7.3800+7.3800Yes50d ago
loop7-weather-features
feature-extraction
CAISO1.9200+1.9200Yes50d ago
loop7-weather-features
feature-extraction
NYISO0.3800+0.3800Yes50d ago
loop7-weather-features
feature-extraction
NYISO0.1890+0.1890Yes50d ago
loop7-weather-features
feature-extraction
NYISO0.00000.0000Yes50d ago
loop7-weather-features
feature-extraction
NYISO21.6700+21.6700Yes50d ago
loop7-weather-features
feature-extraction
ISO_NE0.1860+0.1860Yes50d ago
price_forecasting
foundation llm zero
NYISO8.4928+1.2979Yes51d ago
price_forecasting
baseline
ERCOT12.1589-0.8547Yes51d ago
price_forecasting
foundation llm few
CAISO6.6275+0.9363Yes51d ago
price_forecasting
ml feature search
NYISO9.6065-0.8830Yes51d ago
price_forecasting
foundation llm few
ISO_NE7.3210-0.8103Yes51d ago
price_forecasting
ml feature search
MISO8.0518+1.1133Yes51d ago
price_forecasting
foundation llm zero
SPP9.0359-0.9002No51d ago
price_forecasting
foundation llm zero
CAISO8.8606+0.7756No51d ago
price_forecasting
baseline
PJM10.1990+0.1116Yes51d ago
price_forecasting
ml feature search
ISO_NE7.7550+0.4096Yes51d ago
price_forecasting
ml feature discovery
PJM9.0554-0.2510No51d ago
price_forecasting
foundation llm zero
PJM7.8736-0.8494No51d ago
price_forecasting
ml feature discovery
ISO_NE7.4034-0.9146Yes51d ago
price_forecasting
ensemble
ISO_NE5.0462-0.2759Yes51d ago
price_forecasting
statistical
NYISO9.8290-1.3045Yes51d ago
price_forecasting
foundation llm few
PJM6.3242+1.3528No51d ago
price_forecasting
statistical
MISO9.2923-0.1103Yes51d ago
price_forecasting
ensemble
MISO5.7718-0.8941Yes51d ago
price_forecasting
ensemble
ERCOT6.3174+0.3634No51d ago
price_forecasting
ensemble
PJM4.2239-0.6100No51d ago
price_forecasting
ensemble
CAISO6.2473-0.4166Yes52d ago
price_forecasting
foundation llm few
SPP7.2736-1.0079Yes52d ago
price_forecasting
statistical
SPP8.5462+0.7204No52d ago
price_forecasting
foundation llm zero
ISO_NE9.1524+0.5895Yes52d ago
price_forecasting
baseline
SPP10.8223+0.5573Yes52d ago
price_forecasting
ml feature search
ERCOT8.1581-1.2549Yes52d ago
price_forecasting
ml feature search
CAISO7.6818-0.0776No52d ago
price_forecasting
baseline
NYISO9.9044-0.9180Yes52d ago
price_forecasting
baseline
CAISO13.7481-0.6380Yes52d ago
price_forecasting
ml feature discovery
MISO7.6896-0.4877No52d ago
price_forecasting
ml feature search
PJM7.2153+0.3575No52d ago
price_forecasting
statistical
ISO_NE10.9823+1.2740Yes52d ago
price_forecasting
ml feature discovery
SPP5.9756+1.0141Yes52d ago
price_forecasting
ensemble
SPP4.0926+0.6282No52d ago
price_forecasting
baseline
MISO9.9801-0.4610Yes52d ago
price_forecasting
baseline
ISO_NE13.9604-1.1626Yes52d ago
price_forecasting
foundation llm few
ERCOT9.7936-0.6592No52d ago
price_forecasting
ml feature search
SPP9.8145+0.0172No52d ago
price_forecasting
foundation llm few
NYISO10.5758-0.4196Yes52d ago
price_forecasting
ml feature discovery
ERCOT5.7992+0.1072Yes52d ago
price_forecasting
ml feature discovery
CAISO7.7343+0.8088No52d ago
price_forecasting
ml feature discovery
NYISO6.4283+0.4486Yes53d ago
price_forecasting
foundation llm few
MISO7.9499-1.0811Yes53d ago
price_forecasting
statistical
ERCOT9.7658+1.2828Yes53d ago
Timeline