{"id":"W6910570963","doi":"10.48550/arxiv.1406.2288","title":"Canadian Hydrogen Intensity Mapping Experiment (CHIME) Pathfinder","year":2014,"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":"Pathfinder; Observatory; Spectrograph; Sky; Intensity mapping; Redshift; High dynamic range","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":[0.001577207,0.0008140136,0.0005758563,0.001069776,0.003762261,0.001298342,0.001738872,0.0005887832,0.01188432],"category_scores_gemma":[0.001369946,0.0004032874,0.0003206273,0.00178256,0.001109271,0.001101491,0.001485625,0.001275641,0.002240329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009947834,"about_ca_system_score_gemma":0.02136576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8340434,"about_ca_topic_score_gemma":0.9263406,"domain_scores_codex":[0.9986764,0.00007387678,0.000009807989,0.000230401,0.0007988233,0.0002106807],"domain_scores_gemma":[0.9984875,0.00005248748,0.0000568435,0.0001731678,0.0009507822,0.0002790929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001744791,0.000386372,0.04453857,0.000281309,0.0002006652,0.0003406135,0.0005142505,0.004036884,0.02433338,0.02648037,0.7541371,0.1430057],"study_design_scores_gemma":[0.0008186545,0.0002296563,0.1687456,0.00009022268,0.00008863436,0.0002053189,0.0003396943,0.009577091,0.01312538,0.004634863,0.801934,0.0002110712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1859228,0.002398051,0.0500082,0.01066117,0.0009147634,0.0020646,0.3821415,0.0106828,0.3552062],"genre_scores_gemma":[0.4434414,0.002291594,0.1923667,0.003772743,0.0002222293,0.001192823,0.2285894,0.002138416,0.1259847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8340434,"threshold_uncertainty_score":0.3338678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04393665241673867,"score_gpt":0.1669181844390227,"score_spread":0.122981532022284,"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."}}