{"id":"W16934603","doi":"10.1016/j.surg.2006.02.006","title":"Design, Implementation and Control of a Magnetic Levitation Device","year":2008,"lang":"en","type":"dissertation","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Levitation; Magnetic levitation; Control (management); Engineering; Mechanical engineering; Electrical engineering; Computer science; Magnet; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.000679932,0.0008096787,0.0005129094,0.000572132,0.0005790454,0.001260591,0.002168446,0.000935515,0.004148256],"category_scores_gemma":[0.000914917,0.000316265,0.000348333,0.0001565163,0.0003365703,0.0004641892,0.0007627866,0.000449484,0.001946287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004644615,"about_ca_system_score_gemma":0.001091417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001427136,"about_ca_topic_score_gemma":0.0007962761,"domain_scores_codex":[0.9991105,0.00009643289,0.00006196882,0.0002070916,0.0004126791,0.000111274],"domain_scores_gemma":[0.9992274,0.00008869073,0.0001065863,0.0000972629,0.0003913131,0.00008874098],"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":[0.000870383,0.0006073148,0.008657962,0.0008102358,0.0001284335,0.001010273,0.0005033122,0.02328047,0.6047,0.006160664,0.006801794,0.3464691],"study_design_scores_gemma":[0.0004758025,0.008456642,0.01747053,0.0001422831,0.0003673492,0.001736429,0.0003449713,0.3844446,0.4516197,0.001304102,0.1334098,0.000227848],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06831577,0.0004181602,0.9020008,0.0004725266,0.000439643,0.001608972,0.0002073953,0.004585272,0.02195149],"genre_scores_gemma":[0.7566631,0.0002527589,0.2173727,0.0002559797,0.0001088531,0.001704106,0.000277492,0.0002295355,0.02313559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004148256,"threshold_uncertainty_score":0.01387727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01110868867545881,"score_gpt":0.2561867901296287,"score_spread":0.2450781014541699,"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."}}