{"id":"W7144952455","doi":"","title":"OMTI All-Sky Imager Quick-Look Data (Hbeta emission, 486.1nm, 40s) at Athabasca","year":2017,"lang":"en","type":"dataset","venue":"Institutional Repositories DataBase (IRDB)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thermosphere; Filter (signal processing); Mesosphere; Data acquisition; Atmospheric optics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007140206,0.003053105,0.001566064,0.002939191,0.001365999,0.001820453,0.003844346,0.002071318,0.02668163],"category_scores_gemma":[0.002105686,0.000637265,0.001401994,0.005552241,0.000564896,0.001277728,0.001817191,0.001792992,0.05193844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002959281,"about_ca_system_score_gemma":0.003777714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2185998,"about_ca_topic_score_gemma":0.4009009,"domain_scores_codex":[0.9992052,0.00007316463,0.00004827666,0.0002196374,0.0002641402,0.0001896454],"domain_scores_gemma":[0.9988046,0.0001095945,0.00009710406,0.0002973144,0.0005553215,0.0001360395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004470031,0.00002014309,0.000853374,0.0002518166,0.00002582951,0.00002178079,0.00001668733,0.0003709388,0.0001941523,0.0002045932,0.9959264,0.00206957],"study_design_scores_gemma":[0.0001589422,0.00001868819,0.01205387,0.0002971307,0.00006074193,0.00008719827,0.0001469445,0.001554724,0.001236666,0.001251065,0.9830604,0.00007359305],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002853404,0.00007068601,0.00009973422,0.0000452848,0.00002064529,0.0000125672,0.9981969,0.0004621215,0.0008067309],"genre_scores_gemma":[0.000366293,0.00004111126,0.0002245921,0.00001905713,0.000004184472,0.00002859821,0.9986882,0.00004781067,0.000580238],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7814002,"threshold_uncertainty_score":0.4346548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05732962596304755,"score_gpt":0.3450292600801179,"score_spread":0.2876996341170703,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}