{"id":"W2072592181","doi":"10.1016/j.nima.2010.03.100","title":"The calibration of the Sudbury Neutrino Observatory using uniformly distributed radioactive sources","year":2010,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Neutrino Physics Research","field":"Physics and Astronomy","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of Alberta; Laurentian University; University of Sudbury; Queen's University","funders":"Science and Technology Facilities Council; Industry Canada; CMC Microsystems; Northern Ontario Heritage Fund Corporation; U.S. Department of Energy","keywords":"Photodisintegration; Observatory; Physics; Calibration; Neutron; Neutrino; Nuclear physics; Cherenkov radiation; Radiochemistry; Detector; Astronomy; Optics; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001975936,0.0002481298,0.0003226397,0.0001681966,0.001166757,0.0003776088,0.000378172,0.0001162531,0.00002990001],"category_scores_gemma":[0.00003617052,0.0001740026,0.0001258261,0.001303692,0.0005586548,0.0004033419,0.0004792718,0.001569699,2.888943e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002799331,"about_ca_system_score_gemma":0.000146956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001162287,"about_ca_topic_score_gemma":0.00005285326,"domain_scores_codex":[0.9967746,0.0009860886,0.000433708,0.0004227727,0.0006996382,0.0006831626],"domain_scores_gemma":[0.9985327,0.0004706051,0.0002834788,0.0003561066,0.0001956617,0.0001615099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001161814,0.0003565121,0.1077254,0.00002817959,0.0003409065,6.626682e-7,0.0008849133,0.00004711257,0.8079242,0.01542145,0.00002192583,0.06713249],"study_design_scores_gemma":[0.002287768,0.0004103524,0.08843261,0.0001024057,0.00005841732,0.000002307064,0.003367697,0.01443551,0.874302,0.01491819,0.001150668,0.0005320922],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979447,0.0000187827,0.0004452166,0.00007750011,0.0004080002,0.0006342902,0.00004486116,0.00001786835,0.0004087919],"genre_scores_gemma":[0.998875,0.00004896377,0.0007831242,0.00001154132,0.0001775143,0.00003402347,0.000007596192,0.0000388675,0.00002336316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06660039,"threshold_uncertainty_score":0.8973871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04926169041447567,"score_gpt":0.3639925614330324,"score_spread":0.3147308710185568,"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."}}