{"id":"W4238457281","doi":"10.32920/ryerson.14656968","title":"Development and implementation of the linear phase algorithm in a two-dimensional sun-sensor","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pixel; Algorithm; Microcontroller; MATLAB; Position (finance); Computer science; Phase (matter); Image sensor; Consistency (knowledge bases); Computer vision; Computer hardware; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005167929,0.0003012418,0.0002755304,0.0002920194,0.0001963104,0.0007566005,0.0009078684,0.0004907858,0.003066488],"category_scores_gemma":[0.001241732,0.0003642916,0.00024309,0.0003241647,0.000256107,0.0007413635,0.0004478812,0.0005134908,0.0009766476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003870938,"about_ca_system_score_gemma":0.0008880689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001161945,"about_ca_topic_score_gemma":0.001367602,"domain_scores_codex":[0.999634,0.00003258218,0.00001884037,0.00006466412,0.0002305674,0.00001934569],"domain_scores_gemma":[0.9994281,0.0001402624,0.00003682051,0.00008366763,0.0002843645,0.00002670223],"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":[0.0002813354,0.000238419,0.0025093,0.0003775437,0.00007516954,0.0002544353,0.0004229725,0.07646237,0.5599067,0.01295183,0.002519467,0.3440005],"study_design_scores_gemma":[0.0000373133,0.000228742,0.001705512,0.00001987853,0.00001436577,0.0002852283,0.00005034181,0.628426,0.3549866,0.001176103,0.01301573,0.00005414373],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01683607,0.00003362742,0.9798605,0.00004384112,0.00003511624,0.00008645868,0.00003993538,0.001649279,0.001415176],"genre_scores_gemma":[0.08622208,0.00004796637,0.9116911,0.00002765384,0.000005707787,0.00009670973,0.0000768454,0.0001480964,0.001683857],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003066488,"threshold_uncertainty_score":0.01025838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02248952691236129,"score_gpt":0.3220791361852018,"score_spread":0.2995896092728405,"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."}}