{"id":"W3118437588","doi":"10.5281/zenodo.3563512","title":"Locomotion Data Breed4Food: Educational Files","year":2020,"lang":"en","type":"dataset","venue":"Socio-Environmental Systems Modeling","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hendrix Genetics (Canada)","funders":"","keywords":"Gait; Accelerometer; Artificial intelligence; Inertial measurement unit; Computer vision; Gait analysis; Computer science; Physical medicine and rehabilitation; Medicine","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":[0.0005151248,0.00276144,0.001121405,0.001829171,0.0005994527,0.001125934,0.002721576,0.002132303,0.06649027],"category_scores_gemma":[0.002118449,0.0007540804,0.001056367,0.002375012,0.0003988546,0.001221455,0.001742902,0.001474467,0.09247275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008885885,"about_ca_system_score_gemma":0.0009609853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01625138,"about_ca_topic_score_gemma":0.03717721,"domain_scores_codex":[0.9995128,0.00005276321,0.00004585643,0.0001679981,0.0001270462,0.00009359584],"domain_scores_gemma":[0.9992352,0.0001084138,0.00005682641,0.0002864403,0.0001958208,0.0001173854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001278447,0.00006221663,0.001034003,0.0004498506,0.00002054153,0.00004942256,0.00003165084,0.0004987394,0.0004217744,0.000270681,0.9910817,0.005951485],"study_design_scores_gemma":[0.0003098161,0.00008749214,0.01095627,0.0002237548,0.0000314881,0.0002201999,0.0001926446,0.002941491,0.002199884,0.001388079,0.9813761,0.00007281535],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004333601,0.00003561037,0.0002112707,0.00005087012,0.0000350749,0.00002334808,0.9967983,0.00175874,0.0006533805],"genre_scores_gemma":[0.0008706635,0.00002316272,0.0004615892,0.00002649935,0.00000455307,0.00006833466,0.9978077,0.0001196475,0.0006178631],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06649027,"threshold_uncertainty_score":0.2224321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03624905678257415,"score_gpt":0.2280868721846439,"score_spread":0.1918378154020698,"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."}}