{"id":"W2160786740","doi":"10.1103/physrevlett.116.031102","title":"Sound of Dark Matter: Searching for Light Scalars with Resonant-Mass Detectors","year":2016,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Dark Matter and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"Ontario Ministry of Economic Development and Innovation; Government of Canada; National Science Foundation","keywords":"Physics; Dark matter; Oscillation (cell signaling); Scalar (mathematics); Amplitude; Detector; Particle physics; Moduli; Optics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005560838,0.0003609572,0.0004711493,0.0008573275,0.0002782553,0.0008450542,0.0008024536,0.0007712645,0.001128042],"category_scores_gemma":[0.001325993,0.0003221891,0.0002343628,0.0003971737,0.0005989418,0.001150453,0.001000842,0.0004094689,0.0004077913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003041931,"about_ca_system_score_gemma":0.0001169709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001710679,"about_ca_topic_score_gemma":0.0002578213,"domain_scores_codex":[0.9997492,0.00006759468,0.000007245122,0.00008558356,0.00005256513,0.00003777342],"domain_scores_gemma":[0.9996101,0.0001500006,0.00008617645,0.00006503904,0.00003963211,0.00004897134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001267541,0.0002573468,0.04059403,0.0004938792,0.0002543897,0.001159983,0.0007496822,0.005257021,0.6355827,0.1641339,0.00396311,0.1462862],"study_design_scores_gemma":[0.0007090782,0.00138393,0.03271749,0.0001888504,0.0004759142,0.004176492,0.0009038347,0.3031925,0.4083948,0.2066731,0.04084272,0.0003412554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7590392,0.006752528,0.2005434,0.001448832,0.0001972692,0.0001004172,0.0001713329,0.0007974512,0.03094952],"genre_scores_gemma":[0.9399646,0.0005843562,0.05745333,0.0001820123,0.00005842531,0.00003247891,0.00006575929,0.00002027901,0.001638821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001128042,"threshold_uncertainty_score":0.003773689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00962916152676715,"score_gpt":0.2590320473685117,"score_spread":0.2494028858417446,"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."}}