{"id":"W4237408898","doi":"10.1007/978-3-319-29088-1_9","title":"Experimental Analysis","year":2016,"lang":"en","type":"book-chapter","venue":"","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Victoria","funders":"","keywords":"Biometrics; Normalization (sociology); Software deployment; Computer science; Artificial intelligence; Machine learning; Gait; Relation (database); Process (computing); Key (lock); Human–computer interaction; Data mining; Computer security; Software 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":[0.001914768,0.001333021,0.0006823884,0.0021352,0.00179226,0.001153412,0.001238461,0.000901406,0.08530973],"category_scores_gemma":[0.003270036,0.000409944,0.0007215566,0.001779246,0.001285803,0.001078451,0.001164816,0.001101692,0.03619894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008152645,"about_ca_system_score_gemma":0.001387532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002715639,"about_ca_topic_score_gemma":0.002830362,"domain_scores_codex":[0.9975133,0.0001886783,0.0001875918,0.0008111128,0.001017013,0.0002822162],"domain_scores_gemma":[0.9967129,0.0002873385,0.0001003448,0.001094606,0.001696675,0.0001080185],"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":[0.002090928,0.001626785,0.003031947,0.0009963093,0.00008119213,0.000221077,0.000436417,0.001743314,0.6904911,0.01343067,0.04144339,0.2444068],"study_design_scores_gemma":[0.0002116444,0.002423973,0.01967773,0.0002494975,0.0002469095,0.001125342,0.0005923446,0.005724823,0.7043477,0.007800824,0.2574474,0.0001517146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1969768,0.002595742,0.3208121,0.001127927,0.002832149,0.0056682,0.04058636,0.01164982,0.4177509],"genre_scores_gemma":[0.464152,0.00246371,0.1560652,0.001777947,0.0004841703,0.008477244,0.05796881,0.005397444,0.3032136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08530973,"threshold_uncertainty_score":0.2853895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204529220190112,"score_gpt":0.2061069627642314,"score_spread":0.1940616705623303,"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."}}