{"id":"W2982462992","doi":"10.3390/s19214734","title":"Particle Imaging Velocimetry Gyroscope","year":2019,"lang":"en","type":"article","venue":"Sensors","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Gyroscope; Inertial measurement unit; Velocimetry; Particle image velocimetry; Rate integrating gyroscope; Physics; Inertial frame of reference; Noise (video); Accelerometer; Instability; SIGNAL (programming language); Computer science; Acoustics; Engineering; Optics; Aerospace engineering; Artificial intelligence; Turbulence; Vibrating structure gyroscope; Mechanics; Classical 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":[0.0004440069,0.000731424,0.0008781713,0.001222202,0.0003621539,0.0009234899,0.0007234611,0.000765765,0.003146954],"category_scores_gemma":[0.001428986,0.0002567676,0.0002327434,0.0009463338,0.0003071563,0.0006392505,0.0007943575,0.000691049,0.003189216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000406267,"about_ca_system_score_gemma":0.000773797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002071564,"about_ca_topic_score_gemma":0.001417985,"domain_scores_codex":[0.9991622,0.0000819323,0.00003722205,0.0001957899,0.0004790072,0.00004374208],"domain_scores_gemma":[0.9995649,0.00008957127,0.00007435364,0.00006474098,0.000183669,0.00002272832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005263583,0.00009655306,0.008818656,0.0008243187,0.0001018857,0.0002046806,0.0002956231,0.01296711,0.2445345,0.03639515,0.04079516,0.6544401],"study_design_scores_gemma":[0.0001165036,0.0005712496,0.01414752,0.0001819932,0.0001285442,0.0009181903,0.000111834,0.1310747,0.2159568,0.007567998,0.6290568,0.0001678313],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02748117,0.005775724,0.9193345,0.0004515263,0.001596167,0.000357898,0.004268441,0.01068615,0.03004845],"genre_scores_gemma":[0.397997,0.006044926,0.5517417,0.000521216,0.0007652256,0.0006115829,0.005972923,0.0006003823,0.03574498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003146954,"threshold_uncertainty_score":0.01052761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002996151961368206,"score_gpt":0.18990199574274,"score_spread":0.1869058437813718,"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."}}