{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001560591,0.0004095376,0.0004537441,0.0001139843,0.0001708475,0.0001444459,0.0006739454,0.0003434286,0.0008213787],"category_scores_gemma":[0.00001114864,0.0004545001,0.0001553768,0.00008866154,0.00004206635,0.0002611669,0.0002560168,0.0005144381,0.003107025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003465474,"about_ca_system_score_gemma":0.00002843049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000169309,"about_ca_topic_score_gemma":0.000003009485,"domain_scores_codex":[0.9980104,0.00006986297,0.0005718754,0.0005698963,0.0004839633,0.0002939937],"domain_scores_gemma":[0.9989334,0.00003468604,0.0001167761,0.0007304366,0.000006385718,0.0001782881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001022802,0.00004409229,0.00004247437,0.0002944263,0.0002256207,0.00000270142,0.00002680484,0.09656384,0.00004613493,0.00000122613,0.902565,0.0001866582],"study_design_scores_gemma":[0.0001857098,0.00001063303,0.000005140652,0.0001713285,0.0002764506,0.00001302662,0.002624148,0.5247613,4.092378e-7,0.00003355775,0.4713677,0.0005505788],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004386083,0.001200076,0.003725264,0.0001101375,0.0008464369,0.0002755918,0.9932159,0.0001195509,0.00006846782],"genre_scores_gemma":[0.05446145,0.001162807,0.0001025959,0.00005397019,0.001133293,0.00005853005,0.9428906,0.00006283647,0.0000739129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4311973,"threshold_uncertainty_score":0.9997907,"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."}}