{"id":"W3111640766","doi":"10.1016/j.ohx.2020.e00166","title":"Motor-driven autonomous system for controlling beamline iris diaphragm apertures","year":2020,"lang":"en","type":"article","venue":"HardwareX","topic":"Atomic and Molecular Physics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"College of Engineering, Michigan State University; Technische Universität Darmstadt; University of Toronto; Michigan State University","keywords":"Beamline; Optics; Laser; IRIS (biosensor); Spectroscopy; Diaphragm (acoustics); Inertial confinement fusion; Computer science; Aperture (computer memory); Beam (structure); Materials science; Physics; Acoustics; Artificial intelligence; Vibration","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":[0.000625389,0.0004536233,0.0004342903,0.0004377282,0.0003022452,0.0004906228,0.001348392,0.0004333135,0.009437368],"category_scores_gemma":[0.001079179,0.0003614698,0.0001911499,0.0002134573,0.0002887465,0.0005454065,0.0006473575,0.0004172718,0.002307892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005576153,"about_ca_system_score_gemma":0.0006732554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009432147,"about_ca_topic_score_gemma":0.0008604598,"domain_scores_codex":[0.9994383,0.00005664619,0.00004559018,0.0001702736,0.0002273569,0.00006177476],"domain_scores_gemma":[0.999317,0.0001371559,0.0001126412,0.0001503269,0.0002031507,0.00007971824],"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":[0.001067144,0.000161374,0.005887991,0.0005940209,0.00004772362,0.0004232139,0.0007377656,0.006442693,0.7317194,0.006601197,0.01222794,0.2340896],"study_design_scores_gemma":[0.0002688155,0.001416411,0.01403809,0.0000919685,0.00009433263,0.0010958,0.0001177224,0.1906201,0.6403621,0.0006965627,0.1509948,0.0002033501],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1434304,0.0005210174,0.800589,0.0002667156,0.0003218171,0.0009628868,0.0009324066,0.0391046,0.0138712],"genre_scores_gemma":[0.6333392,0.0001835826,0.3438732,0.0001879877,0.00007062477,0.000656914,0.0006036575,0.0006074563,0.02047739],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009437368,"threshold_uncertainty_score":0.03157121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01268060294851767,"score_gpt":0.2257093474945309,"score_spread":0.2130287445460132,"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."}}