{"id":"W7039484296","doi":"","title":"Mise au point et validation d’une approche terrain de prédiction des chargements au dos basée sur des données de laboratoire","year":2022,"lang":"fr","type":"article","venue":"","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Moment (physics); Validation test; Order (exchange)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01895559,0.002836426,0.001962147,0.005763634,0.001563154,0.006380937,0.002746358,0.003041252,0.005747913],"category_scores_gemma":[0.03879919,0.00122924,0.002731768,0.003492085,0.001101379,0.002389825,0.002075313,0.002155058,0.003798903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003189606,"about_ca_system_score_gemma":0.007220828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1113906,"about_ca_topic_score_gemma":0.1235289,"domain_scores_codex":[0.9888819,0.003672139,0.0008096307,0.002835172,0.003325449,0.0004756372],"domain_scores_gemma":[0.9723674,0.01219311,0.00174992,0.002147173,0.0110264,0.000515866],"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":[0.001386203,0.0007378219,0.3175453,0.003278104,0.002177196,0.0005949655,0.002627121,0.06092076,0.02745739,0.003961483,0.0190063,0.5603074],"study_design_scores_gemma":[0.000319783,0.001408553,0.2748657,0.003470283,0.00158794,0.0007730214,0.003934836,0.6243791,0.02238225,0.008495312,0.05789065,0.0004926489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2686515,0.009562793,0.6744974,0.004368762,0.001041756,0.002226392,0.01031325,0.007211681,0.02212637],"genre_scores_gemma":[0.5641338,0.002808206,0.413561,0.0009698458,0.0001641656,0.001090338,0.007744384,0.0003574222,0.009170868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1113906,"threshold_uncertainty_score":0.2214845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037973992653164,"score_gpt":0.2682613490077376,"score_spread":0.1644639497424212,"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."}}