{"id":"W6946202665","doi":"10.25740/3jhw-x180","title":"2014 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly","year":2019,"lang":"en","type":"dataset","venue":"Stanford Digital Repository","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Deliverable; Observatory; Data set; Set (abstract data type); Solar observatory; Scientific instrument; Data processing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002193621,0.0006270106,0.0005311319,0.00002656441,0.0002561297,0.0005019088,0.001436691,0.0005110975,0.000005375833],"category_scores_gemma":[0.0002060149,0.0006522741,0.0002888497,0.00007761269,0.0001211786,0.00006873938,0.0007040541,0.0005293889,0.00002597067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001276385,"about_ca_system_score_gemma":0.0004480171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001868613,"about_ca_topic_score_gemma":0.0001881785,"domain_scores_codex":[0.9971706,0.00005416594,0.0006234295,0.001175752,0.0003660347,0.000609964],"domain_scores_gemma":[0.9971404,0.00007265844,0.0004349742,0.001991482,0.0001815059,0.0001789612],"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":[0.0003104343,0.00009910981,0.005869725,0.0004856607,0.0002236678,0.00002925656,0.000004803525,0.0001142111,0.003364965,0.00000183668,0.9874549,0.002041442],"study_design_scores_gemma":[0.0006923161,0.0003198762,0.00007001653,0.00006887602,0.0001413207,0.00005007163,0.00004912848,0.009752238,0.0004787672,0.000006378386,0.9875876,0.0007834237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003665136,0.002938779,0.004527993,0.00001533069,0.002028933,0.0005770084,0.9856378,0.00004822508,0.0005608394],"genre_scores_gemma":[0.005928302,0.000352114,0.0004150504,0.0001648953,0.0006881807,0.00002750578,0.9887074,0.0001322968,0.003584236],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009638027,"threshold_uncertainty_score":0.9995928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02055241681123355,"score_gpt":0.2528688621657829,"score_spread":0.2323164453545493,"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."}}