{"id":"W2041962007","doi":"10.1371/journal.pone.0065063","title":"Subspace Identification and Classification of Healthy Human Gait","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Support vector machine; Pattern recognition (psychology); Principal component analysis; Artificial intelligence; Linear discriminant analysis; Subspace topology; Discriminant; Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000456131,0.00004035906,0.00008666821,0.00006966272,0.00002552314,0.00001857734,0.00002918833,0.00002717689,0.0001761883],"category_scores_gemma":[0.00000985118,0.00004348341,0.0000141898,0.00009514704,0.00001498908,0.00008631418,0.000003697972,0.00003945315,0.0001348379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001151156,"about_ca_system_score_gemma":0.000001711899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001902714,"about_ca_topic_score_gemma":0.00001543787,"domain_scores_codex":[0.9996355,0.000009947486,0.0001407607,0.00006770941,0.00008652717,0.00005955476],"domain_scores_gemma":[0.9997574,0.000009892493,0.00003445146,0.00009527495,0.00006633988,0.00003661379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[5.408596e-7,0.0001315946,0.004686775,0.0001768189,0.0000610104,3.140157e-8,0.0001037233,0.000007472618,0.9926667,0.0002616804,0.0003409711,0.001562676],"study_design_scores_gemma":[0.0003277631,0.00003921321,0.7951652,0.00009352263,0.0001551145,3.606761e-7,0.0002642297,0.05407346,0.1486018,0.001023779,0.00006819885,0.0001873799],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975208,0.00008159296,0.0003584964,0.0002819949,0.000006883192,0.00009503296,0.000002485002,0.00006849187,0.001584202],"genre_scores_gemma":[0.9991887,0.00009766081,0.0003069587,0.00001497795,0.0000176947,0.00002561789,0.00002748571,0.000007788392,0.0003131282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.844065,"threshold_uncertainty_score":0.1929138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05269528487634448,"score_gpt":0.2348634000248132,"score_spread":0.1821681151484687,"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."}}