{"id":"W3177523571","doi":"","title":"Canadian Hydrogen Intensity Mapping Experiment (CHIME) Update","year":2019,"lang":"en","type":"article","venue":"American Astronomical Society Meeting Abstracts #233","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Intensity mapping; Intensity (physics); Computer science; Physics; Astronomy; 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":[0.006530349,0.00168594,0.001125081,0.003193199,0.002194945,0.003335751,0.004885322,0.001925333,0.02402217],"category_scores_gemma":[0.007249835,0.0008423538,0.0009141272,0.004095755,0.0007757288,0.002000875,0.002147134,0.001527198,0.009317123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01365821,"about_ca_system_score_gemma":0.04259091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.869454,"about_ca_topic_score_gemma":0.9211646,"domain_scores_codex":[0.9979019,0.0001072788,0.00007820335,0.0002314743,0.001416545,0.0002645739],"domain_scores_gemma":[0.9877383,0.000576516,0.000328829,0.0009006044,0.009442723,0.001013022],"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":[0.0001914523,0.00004411178,0.00207333,0.000199058,0.00004259271,0.00003994931,0.00002018117,0.000210261,0.0003987716,0.0006203559,0.9523541,0.04380591],"study_design_scores_gemma":[0.00005106273,0.00001298744,0.005415508,0.00009055527,0.00005526407,0.00003696082,0.00002069327,0.0001298804,0.0005194835,0.0004296176,0.993215,0.00002296309],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.007477073,0.03222076,0.01389489,0.02931193,0.01755979,0.00149679,0.730204,0.006373758,0.161461],"genre_scores_gemma":[0.03282179,0.04042826,0.04315407,0.01929908,0.004697429,0.001878928,0.6682041,0.002407361,0.1871089],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.130546,"threshold_uncertainty_score":0.2626295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003989676330598204,"score_gpt":0.1836595169414179,"score_spread":0.1796698406108197,"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."}}