{"id":"W141727644","doi":"","title":"Flexibility chart: Evaluation on diversity of flexibility in various areas","year":2013,"lang":"en","type":"article","venue":"LNEG repository (National Laboratory of Energy and Geology)","topic":"Peripheral Artery Disease Management","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Flexibility (engineering); Diversity (politics); Chart; Computer science; Mathematics; Political science; Statistics","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":[0.00439109,0.0006426295,0.0004826199,0.008019911,0.0005386801,0.001639943,0.0005528661,0.0005698845,0.00457205],"category_scores_gemma":[0.01515597,0.0001346295,0.0006705575,0.005567052,0.0006899047,0.002511782,0.001544015,0.0005198402,0.0004934241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007500949,"about_ca_system_score_gemma":0.0005459004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001724986,"about_ca_topic_score_gemma":0.001738042,"domain_scores_codex":[0.9957339,0.001406784,0.0004689724,0.0003269687,0.001796192,0.0002671342],"domain_scores_gemma":[0.9863992,0.006842968,0.002306472,0.0009888475,0.002734326,0.0007282614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00186032,0.0003959393,0.3348853,0.000709915,0.0005828923,0.0008773155,0.002056808,0.1666259,0.008507474,0.03100397,0.00989644,0.4425977],"study_design_scores_gemma":[0.0002355778,0.00350335,0.6164792,0.0006183234,0.0004275557,0.001877729,0.007882857,0.256847,0.01804796,0.03381309,0.05978125,0.0004860451],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8213287,0.0006580866,0.1028496,0.0004154153,0.0001066935,0.0006842698,0.009328092,0.001358861,0.06327027],"genre_scores_gemma":[0.9658519,0.0001382632,0.02990663,0.00003583884,0.00002375275,0.0002119524,0.002472983,0.00006233415,0.001296422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008019911,"threshold_uncertainty_score":0.02322257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01717827670232639,"score_gpt":0.2606168643448363,"score_spread":0.2434385876425099,"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."}}