{"id":"W4394635739","doi":"10.48550/arxiv.astro-ph/0104366","title":"Concerning Parameter Estimation Using the Cosmic Microwave Background","year":2001,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Radio Astronomy Observations and Technology","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outlier; Gaussian; Likelihood function; Cosmic microwave background; Estimation theory; Algorithm; Mathematics; Data set; Statistics; Statistical physics; Applied mathematics; Computer science; Anisotropy; Physics","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":[0.005173211,0.001129577,0.001101093,0.001516134,0.0006308519,0.002834318,0.001579966,0.000911755,0.00314781],"category_scores_gemma":[0.05510567,0.0005443092,0.0008819805,0.002074807,0.001123662,0.003581432,0.001858961,0.002020112,0.001193416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006268268,"about_ca_system_score_gemma":0.0008570681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004728288,"about_ca_topic_score_gemma":0.003693286,"domain_scores_codex":[0.9973072,0.001537465,0.0001098231,0.0003883706,0.000531591,0.0001256122],"domain_scores_gemma":[0.9880414,0.008452349,0.0005728215,0.002094463,0.0007050537,0.00013398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002430276,0.00004643273,0.02008137,0.0004713419,0.0003798243,0.0003658739,0.0005284405,0.3377643,0.008816446,0.2779073,0.005639463,0.3477562],"study_design_scores_gemma":[0.00003229312,0.00005338386,0.009357073,0.0001663498,0.00004861327,0.000437421,0.0002649732,0.5975107,0.01234681,0.3635967,0.01606361,0.0001220406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02347123,0.001057154,0.9699907,0.0009602733,0.00006434344,0.000014128,0.0002973344,0.0009464736,0.003198389],"genre_scores_gemma":[0.3629679,0.001883102,0.6290948,0.0005363162,0.0002320412,0.0000855478,0.001358317,0.001107166,0.002734781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005173211,"threshold_uncertainty_score":0.02735883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175405528705212,"score_gpt":0.2172529108945158,"score_spread":0.09971235802399452,"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."}}