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 {"tstamp": 1722435824.195, "task_type": "retrieval", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722435823.6918, "finish": 1722435824.195, "ip": "", "conv_id": "b3487cab0720415f8e58696097136d9c", "model_name": "embed-english-v3.0", "prompt": "Orca life expectancy", "output": [["Orca life expectancy", "Captive orcas\n\nDisease and lifespan The lifespan of killer whales in captivity versus wild killer whales is disputed.  Several studies published in scientific journals show that the average mortality rate for captive killer whales is approximately three times higher than in the wild. A 2015 study in the Journal of Mammalogy, authored by SeaWorld's vice-president of theriogenology, Todd Robeck, concluded that the life expectancy for killer whales born at SeaWorld is the same as those in the wild. In the wild, female killer whales have a typical lifespan of 60–80 years, and a maximum recorded lifespan of 103 years.  The average lifespan for males in the wild is 30 years, but some live up to 50–60 years. The 2015 study has been criticised by Trevor Willis, senior lecturer in marine biology at the University of Portsmouth, who stated that the study is misleading, \"clearly wrong\" and indicative of \"poor practice\".  He stated that it is misleading in two ways: \"First, it compares two completely different circumstances: the controlled environment of a swimming pool, with highly trained vets on hand; and the wild ocean. \"There are no predators in a swimming pool. Second, and in the absence of any other information, it appears they've looked at the survival rate of calves in the first two years of life and extrapolated it out 50 years into the future.\" He also stated that no captive orca has lived for 55.8 years, the recorded average life expectancy of adult orcas at SeaWorld."]], "corpus": "wikipedia"}
 {"tstamp": 1722435933.2884, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722435933.1316, "finish": 1722435933.2884, "ip": "", "conv_id": "bc9d5486eaed40f8be91f71650db13c7", "model_name": "BM25", "prompt": "The best Sentinel-2 bands for wildfire-burned area segmentation", "output": [["The best Sentinel-2 bands for wildfire-burned area segmentation", "Title: Sen2Fire: A Challenging Benchmark Dataset for Wildfire Detection using Sentinel Data\n\nAbstract: Utilizing satellite imagery for wildfire detection presents substantial potential for practical applications. To advance the development of machine learning algorithms in this domain, our study introduces the \\textit{Sen2Fire} dataset--a challenging satellite remote sensing dataset tailored for wildfire detection. This dataset is curated from Sentinel-2 multi-spectral data and Sentinel-5P aerosol product, comprising a total of 2466 image patches. Each patch has a size of 512$\\times$512 pixels with 13 bands. Given the distinctive sensitivities of various wavebands to wildfire responses, our research focuses on optimizing wildfire detection by evaluating different wavebands and employing a combination of spectral indices, such as normalized burn ratio (NBR) and normalized difference vegetation index (NDVI). The results suggest that, in contrast to using all bands for wildfire detection, selecting specific band combinations yields superior performance. Additionally, our study underscores the positive impact of integrating Sentinel-5 aerosol data for wildfire detection. The code and dataset are available online (https://zenodo.org/records/10881058)."]], "corpus": "arxiv"}
 {"tstamp": 1722435933.2884, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722435933.1316, "finish": 1722435933.2884, "ip": "", "conv_id": "d679afd9ac124e39a9e06dbe8710a5ff", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "The best Sentinel-2 bands for wildfire-burned area segmentation", "output": [["The best Sentinel-2 bands for wildfire-burned area segmentation", "Title: Robust Burned Area Delineation through Multitask Learning\n\nAbstract: In recent years, wildfires have posed a significant challenge due to their increasing frequency and severity. For this reason, accurate delineation of burned areas is crucial for environmental monitoring and post-fire assessment. However, traditional approaches relying on binary segmentation models often struggle to achieve robust and accurate results, especially when trained from scratch, due to limited resources and the inherent imbalance of this segmentation task. We propose to address these limitations in two ways: first, we construct an ad-hoc dataset to cope with the limited resources, combining information from Sentinel-2 feeds with Copernicus activations and other data sources. In this dataset, we provide annotations for multiple tasks, including burned area delineation and land cover segmentation. Second, we propose a multitask learning framework that incorporates land cover classification as an auxiliary task to enhance the robustness and performance of the burned area segmentation models. We compare the performance of different models, including UPerNet and SegFormer, demonstrating the effectiveness of our approach in comparison to standard binary segmentation."]], "corpus": "arxiv"}
+{"tstamp": 1722445108.5632, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722445108.2586, "finish": 1722445108.5632, "ip": "", "conv_id": "e5dc54f50f85414484339a9b0ce90ef8", "model_name": "GritLM/GritLM-7B", "prompt": "how to write time and date in military", "output": [["how to write time and date in military", "Date-time group\n\nMilitary Date Time Group A form of DTG is used in the US Military's message traffic (a form of Automated Message Handling System). In US military messages and communications (e.g., on maps showing troop movements) the format is DD HHMM (SS) Z MON YY. Although occasionally seen with spaces, it can also be written as a single string of characters. Three different formats can be found:\n- Full time (used for software timestamps)\n- shortened time (used e.g. for timestamps manually written)\n- short time (e.g. used for planning)\nreferences the military identifier of time zone:\nUTC-12: Y (e.g., Baker Island)\nUTC-11: X (American Samoa, Niue)\nUTC-10: W (Honolulu, HI)\nUTC-9: V (Juneau, AK)\nUTC-8: U (PST, Los Angeles, CA)\nUTC-7: T (MST, Denver, CO)\nUTC-6: S (CST, Dallas, TX)\nUTC-5: R (EST, New York, NY)\nUTC-4: Q (Halifax, Nova Scotia)\nUTC-3: P (Buenos Aires, Argentina; Rio de Janeiro, Brazil)\nUTC-2: O (South Georgia and the South Sandwich Islands)\nUTC-1: N (Azores)\nUTC+-0: Z (Zulu time)\nUTC+1: A (France)\nUTC+2: B (Athens, Greece)\nUTC+3: C (Arab Standard Time, Iraq, Bahrain, Kuwait, Saudi Arabia, Yemen, Qatar, as well as Moscow in Russia)\nUTC+4: D (Oman, the UAE)\nUTC+5: E (Pakistan, western Kazakhstan, Tajikistan, Uzbekistan, and Turkmenistan)\nUTC+6: F (eastern Kazakhstan, Bangladesh)\nUTC+7: G (Thailand)\nUTC+8: H (Beijing, China, Singapore)\nUTC+9: I (Tokyo, Japan)\nUTC+10: K (Brisbane, Australia)\nUTC+11: L (Sydney, Australia)\nUTC+12: M (Wellington, New Zealand)\nExamples\nExample 1:  represents the 5th day of the current month 11:00 (UTC).\nExample 2:  represents  9 July 2011 4:30 pm (MST).\nExample 3:  represents the current time of refresh:  (UTC)."]], "corpus": "wikipedia"}
+{"tstamp": 1722445108.5632, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1722445108.2586, "finish": 1722445108.5632, "ip": "", "conv_id": "941220ab10f8447faa3721af54701b53", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "how to write time and date in military", "output": [["how to write time and date in military", "List of Dutch inventions and innovations\n\nAn artificial kidney is a machine and its related devices which clean blood for patients who have an acute or chronic failure of their kidneys. The first artificial kidney was developed by Dutchman Willem Johan Kolff. The procedure of cleaning the blood by this means is called dialysis, a type of renal replacement therapy that is used to provide an artificial replacement for lost kidney function due to renal failure. It is a life support treatment and does not treat disease.\nArtificial heart (1957)\nOn 12 December 1957, Kolff implanted an artificial heart into a dog at Cleveland Clinic. The dog lived for 90 minutes. In 1967, Dr. Kolff left Cleveland Clinic to start the Division of Artificial Organs at the University of Utah and pursue his work on the artificial heart. Under his supervision, a team of surgeons, chemists, physicists and bioengineers developed an artificial heart and made it ready for industrial production. To help manage his many endeavors, Dr. Kolff assigned project managers. Each project was named after its manager. Graduate student Robert Jarvik was the project manager for the artificial heart, which was subsequently renamed the Jarvik-7. Based on lengthy animal trials, this first artificial heart was successfully implanted into the thorax of patient Barney Clark in December 1982. Clark survived 112 days with the device.\nMilitary"]], "corpus": "wikipedia"}