{"id":"W3049761375","doi":"","title":"Metis: Coronagraph Performance & Coordinated Observations","year":2019,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metis; Coronagraph; Geography; Astronomy; Computer science; Physics; Exoplanet; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001609688,0.0001343441,0.0001309878,0.00005854395,0.00006925432,0.00002440927,0.0001113544,0.00008840589,0.000008209304],"category_scores_gemma":[0.00003942253,0.0001389564,0.00004262772,0.0002223239,0.00001290888,0.0002156366,0.00001124278,0.0001811657,0.0004205845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003992966,"about_ca_system_score_gemma":0.000007923429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008415162,"about_ca_topic_score_gemma":0.0002151219,"domain_scores_codex":[0.9991752,0.00001185361,0.0002689517,0.0001405946,0.0001443195,0.0002590693],"domain_scores_gemma":[0.9995829,0.00006910221,0.00005016581,0.0001683095,0.00007093066,0.00005860882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00001500864,0.00003405055,0.2957696,0.000187778,0.00006252983,0.000006550926,0.0003418966,0.5868101,0.1115862,0.0001528894,0.001132937,0.003900427],"study_design_scores_gemma":[0.000348967,0.00004209332,0.9237872,0.0001621351,0.00002147072,0.000005554571,0.00005299265,0.04865068,0.0228312,0.00003131147,0.003765471,0.0003009679],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649577,0.0001115501,0.00001609815,0.00003666941,0.0005239266,0.0001589005,0.000003757438,0.0004390615,0.03375239],"genre_scores_gemma":[0.9989345,0.00004409114,0.0005087575,0.0000496395,0.00007387943,0.00000825058,0.00004814888,0.0000305691,0.0003021791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6280175,"threshold_uncertainty_score":0.5666476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01435095540116761,"score_gpt":0.2070485353897711,"score_spread":0.1926975799886035,"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."}}