{"id":"W1970586850","doi":"10.1016/s1440-2440(04)80009-4","title":"Enhancing specificity in proxy-design for the assessment of bioenergetics","year":2004,"lang":"en","type":"article","venue":"Journal of science and medicine in sport","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"","keywords":"Bioenergetics; Proxy (statistics); Biochemical engineering; Computer science; Engineering; Chemistry; Biochemistry; Machine learning","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":[0.07254591,0.001267654,0.00146142,0.001063231,0.0008701825,0.002684333,0.001284322,0.002066739,0.004342663],"category_scores_gemma":[0.1856844,0.001108672,0.001185568,0.0009877044,0.001285072,0.001572911,0.003584052,0.001748573,0.001938372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005473648,"about_ca_system_score_gemma":0.001239591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004271851,"about_ca_topic_score_gemma":0.0008818304,"domain_scores_codex":[0.9019776,0.08416089,0.004715305,0.004225011,0.004049412,0.0008718353],"domain_scores_gemma":[0.8375341,0.1204467,0.006812686,0.02230277,0.01173548,0.001168165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01566976,0.003343691,0.2919469,0.001982952,0.001524303,0.0002752535,0.00590387,0.02067073,0.04999349,0.03691817,0.004146799,0.5676241],"study_design_scores_gemma":[0.004550579,0.01621437,0.3868411,0.0009342917,0.001859028,0.002427239,0.001840957,0.3263392,0.1418149,0.07467042,0.04193351,0.0005742941],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1096774,0.0001888466,0.8837602,0.0002348038,0.0001547113,0.00182782,0.0002194471,0.000674932,0.003261819],"genre_scores_gemma":[0.4731757,0.00009349202,0.5185826,0.0003902694,0.00007535615,0.00527622,0.000295874,0.0003825551,0.001727966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07254591,"threshold_uncertainty_score":0.383664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05224888675365634,"score_gpt":0.3696434020539482,"score_spread":0.3173945153002918,"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."}}