{"id":"W2161039927","doi":"10.1109/icdsp.2009.5201167","title":"Wavelet analysis of cyclic human gait for recognition","year":2009,"lang":"en","type":"article","venue":"","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Biometrics; Gait; Artificial intelligence; Computer science; Computer vision; Wavelet; Gait analysis; Feature (linguistics); Feature extraction; Face (sociological concept); Pattern recognition (psychology); Limelight; Engineering; Physical medicine and rehabilitation","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":[0.0001531865,0.0002271386,0.0002206049,0.0006547309,0.00008501761,0.0002412043,0.0001372477,0.0002012771,0.002266745],"category_scores_gemma":[0.0006707218,0.00008446447,0.0002405873,0.0009027352,0.000134413,0.0002954846,0.0001413689,0.0002199574,0.0007233797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001033882,"about_ca_system_score_gemma":0.0001773138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006307792,"about_ca_topic_score_gemma":0.0007302591,"domain_scores_codex":[0.9999055,0.00001329993,0.000007698876,0.00001528939,0.00004621317,0.00001191389],"domain_scores_gemma":[0.9998406,0.00003389648,0.00002539448,0.00002630482,0.00006429698,0.000009579214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001718372,0.0000779466,0.002979378,0.0002524914,0.00003764951,0.0003090887,0.00008363956,0.0142764,0.3277934,0.006243333,0.004296598,0.6434783],"study_design_scores_gemma":[0.0000283516,0.0005216719,0.03872995,0.000114138,0.00009251381,0.002474214,0.0001882019,0.7759052,0.1408543,0.007596999,0.03342985,0.00006468978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2094599,0.001473771,0.7817496,0.0002956237,0.0002501775,0.00005859865,0.0004861208,0.0007682891,0.005457902],"genre_scores_gemma":[0.7594132,0.001924853,0.2317566,0.00007859404,0.000124371,0.00005693113,0.0009181646,0.0001031757,0.005624019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002266745,"threshold_uncertainty_score":0.007582963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02330738712565205,"score_gpt":0.2560268961203955,"score_spread":0.2327195089947435,"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."}}